If you searched for data enrichment api, you probably want a ranked answer, not a definition. You want to know which API is worth wiring into your system, what it costs, where the data goes stale, and which products create extra implementation work later. My answer is NinjaPear. Not because it wins every subcategory, but because it combines company data, employee data, relationship data, change monitoring, and unusually strong AI-agent readiness in one product.
The API itself matters less than how often the data drifts and how ugly the field mapping gets once you start pushing it into a real CRM.
That is the real buying problem: drift and workflow fit.
A working spreadsheet with pricing notes, refresh math, monthly volume planning, and an AI-docs checklist for 25 vendors.
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Quick rankings
Here is the ranked list first.
- NinjaPear
- EnrichmentAPI
- People Data Labs
- Apollo
- Clearbit
- ZoomInfo
- FullContact
- Hunter
- Clay
- Crunchbase
- Cognism
- RocketReach
- UpLead
- Dropcontact
- Clearout
- Snov.io
- Lusha
- ContactOut
- LeadMagic
- Kaspr
- Prospeo
- Adapt.io
- Seamless.AI
- Datagma
- Coresignal
This lines up with how many buyers already scan the market.
the more ‘established’ ones I’ve seen used a lot: Clearbit, Apollo, ZoomInfo, Crunchbase, People Data Labs
That shortlist is reasonable. It is also incomplete.
The real split in 2026 is this:
- dataset vendors
- live enrichment vendors
- prospecting tools with an API attached
- intelligence products that also track what changed
Those are not the same thing. Buyers still compare them like they are.
How I ranked them
I used seven dimensions:
- Freshness
- Richness
- Scalability
- Pricing clarity
- Developer friendliness
- Stability
- AI readiness
Freshness is obvious. Old data degrades quickly.
Richness is not about who has the longest field list. It is whether the returned fields help you do real work.
Scalability is whether I would trust the product inside a system, not whether the vendor sells to large companies.
Pricing clarity matters because hidden pricing usually means forecasting pain, longer sales cycles, or both.
Developer friendliness is docs, schemas, errors, auth flow, rate limits, timeout behavior, and how messy the async model gets.
Stability is whether the product feels like dependable infrastructure.
AI readiness is now part of API quality. If your docs are hard for Claude, Cursor, Codex, or ChatGPT to ingest, integration gets slower.
Pricing table
Pricing belongs near the top because this is where vendors either respect your time or don’t.
If a company hides pricing, I count that against them. Not because every custom contract is bad. Because in a category this mature, hiding entry-level economics is usually a sign that evaluation will be slower and harder than it needs to be.
| Vendor | Public starting price | API access | Pricing style | Opaque? | Notes |
|---|---|---|---|---|---|
| NinjaPear | Trial + $49/mo tier or PAYG | Yes | Credit-based | No | 3-day trial, 10 credits, PAYG valid 18 months, subscriptions require 12-month commitment |
| EnrichmentAPI | $99 | Yes | Credit-based | No | Person API 5 credits, Company API 5, Employees API 10, retries up to 60s |
| People Data Labs | ~$98/mo person, ~$100/mo company | Yes | Credit-based | No | Transparent credit logic, but freshness is more dataset-style than live-style |
| Apollo | $49/seat/mo basic, API on custom | Partial | Seat + custom API | Partial | Seat pricing public, real API usage gets sales-led fast |
| Clearbit | Custom / opaque | Yes | Custom | Yes | No clean self-serve API pricing |
| ZoomInfo | Custom / opaque | Yes | Custom | Yes | Enterprise sales motion, no public API pricing |
| FullContact | Custom / opaque | Yes | Custom | Yes | Different category, same opaque buying motion |
| Hunter | $49/mo monthly, $34/mo annual starter | Yes | Credit-based | No | Clear pricing, clear email economics |
| Clay | Custom usage varies | Partial | Credits + provider costs | Partial | Entry pricing exists, real cost depends on stack |
| Crunchbase | Mixed / limited visibility | Yes | Plan + API access | Partial | Useful company data, API economics not clean publicly |
| Cognism | From ~$12,000/yr in public CRM enrichment content | Yes | Contract + credits | Partial | Contract-first |
| RocketReach | Plans start ~$6k annually for higher API limits | Yes | Mixed | Partial | Public plans exist, API cost less obvious |
| UpLead | Public plans, API included by plan | Yes | Seat + credits | Partial | More visible than enterprise vendors, still fuzzy |
| Dropcontact | ~€24/mo | Yes | Pay on success | No | You pay when it finds or verifies an email |
| Clearout | $19.5/mo monthly, $16/mo annual starter | Yes | PAYG + subscription | No | Unused credits roll over and do not expire |
| Snov.io | ~$39/mo | Partial | Seat + credits | No | Cheap to try, not infra-grade |
| Lusha | Public plans, API less central | Partial | Seat + credits | Partial | More SDR tool than API product |
| ContactOut | $99/mo email, $199/mo email + phone | Yes | Plan-based | No | People-first |
| LeadMagic | $49/mo | Yes | Pay per result | No | Good for waterfall buyers |
| Kaspr | €45/mo | Starter+ | Seat + credits | No | API starts from Starter |
| Prospeo | Public credit pricing | Yes | Credits | No | Small-team-friendly |
| Adapt.io | Free, $49, $99 public tiers | Yes | Seat + credits | No | Public enough, just not very active-feeling |
| Seamless.AI | Free trial, serious pricing sales-led | Yes | Trial + contract | Partial | High awareness, pricing gets vague |
| Datagma | $39/mo billed yearly | Yes | Credits | No | Lower-cost API-first option |
| Coresignal | $49/mo API starting point | Yes | API + datasets | No | Broader dataset cost varies |
A few takeaways:
- NinjaPear, EnrichmentAPI, Hunter, Clearout, LeadMagic, Prospeo, and Datagma let you estimate cost without a sales call.
- Clearbit, ZoomInfo, and FullContact lose points because hidden pricing slows evaluation.
- Apollo, Clay, Cognism, and RocketReach sit in the middle: enough public info to get interested, not enough to forecast neatly.
1. NinjaPear
What it does
NinjaPear ranks first because it does more than one-time append. Company details. Employee profiles. Customer relationships. Competitors. Monitoring. That last part matters because after enrichment, the next operational question is usually what changed.
How I scored it
I scored freshness 5/5 because the public product and docs are built around current company intelligence plus ongoing updates, not just static appends. I scored richness 4/5 because it covers company, employee, relationship, and monitoring data, but it is not pretending to be a universal contact database. Dev-friendliness is 5/5 because the docs expose Markdown docs, llms.txt, OpenAPI, SDKs, rate-limit guidance, timeout guidance, and explicit error codes. AI readiness is 5/5 because it is the only vendor here with clear public evidence across all five AI criteria.
Pricing
3-day free trial with 10 credits. Public tiers at $49, $299, $899, and $1,899 per month. PAYG credits last 18 months. Subscriptions come with a 12-month commitment. Customer Listing is 1 credit per request + 2 credits per customer returned.
AI dimension
- AI Skill: Yes
- MCP or agent path: Yes
- Markdown docs: Yes
llms.txt: Yes- OpenAPI spec: Yes
What I like
It feels built for builders. Relationship data plus monitoring is a real differentiator. Most vendors stop at returning a record. NinjaPear gets closer to answering why the account matters now.
What will annoy you
If all you need is basic email append, this is more product than you need. Also, the subscription commitment is explicit and real.
Best for
Teams that care about company intelligence, timing, and AI-assisted implementation.
User signal
Public market discussion around GTM tools keeps drifting toward workflow fit, not just data size. That matches why NinjaPear ranks first here: it behaves more like a system input than a list vendor.
Star rating summary
Freshness ⭐⭐⭐⭐⭐ (5/5) | Richness ⭐⭐⭐⭐☆ (4/5) | Scalability ⭐⭐⭐⭐☆ (4/5) | Pricing ⭐⭐⭐⭐☆ (4/5) | Dev ⭐⭐⭐⭐⭐ (5/5) | Stability ⭐⭐⭐⭐☆ (4/5) | AI ⭐⭐⭐⭐⭐ (5/5)
2. EnrichmentAPI
What it does
EnrichmentAPI is a generic enrichment API for person, company, employees, tech stack, and reverse email lookups.
How I scored it
I scored freshness 4/5 because the vendor positions the product as live enrichment and the docs discuss request retries and timeout behavior, which is at least evidence of request-time processing rather than only serving warehouse snapshots. I scored dev-friendliness 4/5 because the docs expose credit costs and ugly operational details. I held stability to 3/5 because docs explicitly mention 408s on ~1-2% of requests, which is honest but still an integration burden. AI readiness is 1/5 because I found no public evidence of agent-specific documentation assets.
Pricing
Starts at $99. Person API 5 credits, Company API 5, Employees API 10, Company Investment 1, Tech Stack 1.
AI dimension
- AI Skill: No clear public evidence found
- MCP or agent path: No clear public evidence found
- Markdown docs: No clear public evidence found
llms.txt: No clear public evidence found- OpenAPI spec: No clear public evidence found
What I like
The docs disclose operational tradeoffs more clearly than most vendors do.
What will annoy you
Docs say requests may retry for up to 60 seconds, and 408s happen on roughly 1-2% of requests. So you need to engineer for that.
Best for
People who want a generic enrichment API with visible pricing and visible docs.
User signal
The strongest thing I can say here is that EnrichmentAPI is candid in docs where many competitors are vague. That matters. It reduces surprises.
Star rating summary
Freshness ⭐⭐⭐⭐☆ (4/5) | Richness ⭐⭐⭐⭐☆ (4/5) | Scalability ⭐⭐⭐⭐☆ (4/5) | Pricing ⭐⭐⭐⭐☆ (4/5) | Dev ⭐⭐⭐⭐☆ (4/5) | Stability ⭐⭐⭐☆☆ (3/5) | AI ⭐☆☆☆☆ (1/5)
3. People Data Labs
What it does
People Data Labs is builder infrastructure. Breadth. Scale. APIs designed for teams that will actually integrate and reprocess data.
How I scored it
I scored scalability 5/5 because the pricing docs, bulk API logic, and product structure clearly support larger-volume workflows. I scored freshness 3/5 because the company side still feels dataset-first, and PDL’s own ecosystem includes scheduled refresh cadences rather than a stronger live-change story. Dev-friendliness is 5/5 because the pricing docs are unusually explicit, credits are easy to model, and the API product feels like infra. AI readiness is 2/5 because the docs are strong for humans, but I found no public llms.txt, agent skill, or equivalent machine-first AI layer.
Pricing
Public pricing shows person enrichment from $98/mo for 350 credits and company enrichment from $100/mo for 1,000 credits. Docs explain credit logic clearly: successful matches generally consume 1 credit.
AI dimension
- AI Skill: No clear public evidence found
- MCP or agent path: No clear public evidence found
- Markdown docs: No clear public evidence found
llms.txt: No clear public evidence found- OpenAPI spec: No clear public evidence found
What I like
Good API posture. Good pricing clarity. Serious infrastructure feel.
What will annoy you
Freshness tradeoff. This feels more like a dataset company with APIs than a live-change product.
You should also be honest about sourcing risk. PDL has long been associated with LinkedIn data in the market conversation. If your legal team cares, read this: Is scraping LinkedIn legal in 2026?
Best for
Builders who want scale and broad coverage more than live-change intelligence.
User signal
The market keeps using PDL as the serious builder benchmark. That reputation is deserved on infra and API design. It is less strong on freshness.
Star rating summary
Freshness ⭐⭐⭐☆☆ (3/5) | Richness ⭐⭐⭐⭐☆ (4/5) | Scalability ⭐⭐⭐⭐⭐ (5/5) | Pricing ⭐⭐⭐☆☆ (3/5) | Dev ⭐⭐⭐⭐⭐ (5/5) | Stability ⭐⭐⭐⭐⭐ (5/5) | AI ⭐⭐☆☆☆ (2/5)
4. Apollo
What it does
Apollo is the default all-in-one outbound tool. Prospecting database, sequences, enrichment, the whole thing.
How I scored it
I scored richness 4/5 because Apollo covers person, company, and contact data well enough for a broad outbound workflow. I scored dev-friendliness 2/5 because the API starts clean but gets more complex once you use waterfall enrichment. Public docs explicitly state that when waterfall parameters are used, Apollo returns synchronous demographic and firmographic data first, then delivers email and phone enrichment asynchronously to a configured webhook. That is real complexity. Pricing is 3/5 because seats are public but serious API usage moves into custom territory.
Pricing
Basic $49, Professional $79, Organization $119 per seat monthly, billed annually. API for advanced use cases is on Custom plans.
AI dimension
- AI Skill: No clear public evidence found
- MCP or agent path: No clear public evidence found
- Markdown docs: No clear public evidence found
llms.txt: No clear public evidence found- OpenAPI spec: No clear public evidence found
What I like
It works well enough to stay on a lot of shortlists.
What will annoy you
API ergonomics get more complex when you move past the happy path. Waterfall email and phone enrichment can come back asynchronously via webhook, and Apollo may retry webhook calls, so your endpoint needs idempotency.
apollo enrichment is a headache man especially with small lists i just skip it now ... so the list is usable without babysitting the workflow
That is a fair description of Apollo.
Best for
Teams that want convenience first.
Star rating summary
Freshness ⭐⭐☆☆☆ (2/5) | Richness ⭐⭐⭐⭐☆ (4/5) | Scalability ⭐⭐⭐⭐☆ (4/5) | Pricing ⭐⭐⭐☆☆ (3/5) | Dev ⭐⭐☆☆☆ (2/5) | Stability ⭐⭐⭐⭐☆ (4/5) | AI ⭐☆☆☆☆ (1/5)
5. Clearbit
What it does
Clearbit is still relevant for company enrichment and routing workflows, especially in HubSpot-heavy stacks.
How I scored it
I scored freshness 4/5 because Clearbit still has a strong reputation in routing and form enrichment workflows where fast company resolution matters. I scored pricing 2/5 because public API economics are no longer easy to evaluate. I scored stability 5/5 because despite the buying-motion frustration, the product has years of operational credibility in this category.
Pricing
Opaque.
AI dimension
- AI Skill: No clear public evidence found
- MCP or agent path: No clear public evidence found
- Markdown docs: No clear public evidence found
llms.txt: No clear public evidence found- OpenAPI spec: No clear public evidence found
What I like
Good operating history in company enrichment and routing.
What will annoy you
The buying motion. Hidden pricing. Less self-serve. More platform gravity.
Best for
HubSpot-heavy teams doing routing and standard firmographics.
User signal
Clearbit still shows up constantly in buyer shortlists. The issue is not relevance. It is evaluation friction.
Star rating summary
Freshness ⭐⭐⭐⭐☆ (4/5) | Richness ⭐⭐⭐⭐☆ (4/5) | Scalability ⭐⭐⭐⭐☆ (4/5) | Pricing ⭐⭐☆☆☆ (2/5) | Dev ⭐⭐⭐☆☆ (3/5) | Stability ⭐⭐⭐⭐⭐ (5/5) | AI ⭐☆☆☆☆ (1/5)
6. ZoomInfo
What it does
ZoomInfo is the big enterprise incumbent. Huge dataset. Strong contact story. Enterprise buying motion.
How I scored it
I scored richness and scalability 5/5 because ZoomInfo’s entire value proposition is breadth and enterprise coverage. I scored pricing 1/5 because the API economics are opaque. I scored dev-friendliness 2/5 because enterprise vendors can have capable APIs, but public evaluation is weak and self-serve technical due diligence is harder than it should be. AI readiness stays 1/5 because I found no clear public evidence of an agent-native docs layer.
Pricing
Opaque.
AI dimension
- AI Skill: No clear public evidence found
- MCP or agent path: No clear public evidence found
- Markdown docs: No clear public evidence found
llms.txt: No clear public evidence found- OpenAPI spec: No clear public evidence found
What I like
Coverage, especially for enterprise US sales teams.
What will annoy you
Price opacity. Procurement drag. Contract gravity.
Best for
Large companies that want the incumbent and can pay for it.
User signal
ZoomInfo is still the enterprise default in many orgs. That says a lot about market reach. It says less about ease of evaluation.
Star rating summary
Freshness ⭐⭐⭐☆☆ (3/5) | Richness ⭐⭐⭐⭐⭐ (5/5) | Scalability ⭐⭐⭐⭐⭐ (5/5) | Pricing ⭐☆☆☆☆ (1/5) | Dev ⭐⭐☆☆☆ (2/5) | Stability ⭐⭐⭐⭐⭐ (5/5) | AI ⭐☆☆☆☆ (1/5)
7. FullContact
What it does
FullContact is better thought of as identity resolution infrastructure than a straight SDR enrichment tool.
How I scored it
I scored richness 4/5 because identity stitching can be very valuable in the right stack. I scored pricing 2/5 because public evaluation is still weak. Dev-friendliness is 4/5 because the product is more infrastructure-oriented than many sales-database vendors. AI readiness is 2/5 because while the product category maps well to programmatic use, I found no public evidence of dedicated AI-doc assets.
Pricing
Mostly custom.
AI dimension
- AI Skill: No clear public evidence found
- MCP or agent path: No clear public evidence found
- Markdown docs: No clear public evidence found
llms.txt: No clear public evidence found- OpenAPI spec: No clear public evidence found
What I like
It solves a real identity problem that most prospecting tools don’t.
What will annoy you
If you want a simple contact-data vendor, this is not the cleanest buy.
Best for
Identity stitching and multi-identifier systems.
User signal
FullContact makes more sense to data teams than SDR teams. That is why it ranks mid-pack instead of near the top.
Star rating summary
Freshness ⭐⭐⭐☆☆ (3/5) | Richness ⭐⭐⭐⭐☆ (4/5) | Scalability ⭐⭐⭐⭐☆ (4/5) | Pricing ⭐⭐☆☆☆ (2/5) | Dev ⭐⭐⭐⭐☆ (4/5) | Stability ⭐⭐⭐⭐☆ (4/5) | AI ⭐⭐☆☆☆ (2/5)
8. Hunter
What it does
Hunter is email-first. Finder. Verifier. Domain search. Some enrichment.
How I scored it
I scored pricing and dev-friendliness 4/5 because the public pricing and API credit model are clean. Hunter’s own help docs spell out API credit costs, including 0.5 credit for Email Verifier in one help center article. I scored richness 2/5 because Hunter is narrower than company-intelligence vendors. Stability is 5/5 because it has stayed focused on the problem it actually solves.
Pricing
Starter $49 monthly or $34 annual equivalent, Growth $149 or $104, Scale $299 or $209. Search and verification credits are clearly described publicly.
AI dimension
- AI Skill: No clear public evidence found
- MCP or agent path: No clear public evidence found
- Markdown docs: No clear public evidence found
llms.txt: No clear public evidence found- OpenAPI spec: No clear public evidence found
What I like
It knows what it is.
What will annoy you
It is not broad company intelligence.
Best for
Email-heavy workflows.
User signal
Hunter keeps winning because teams understand what they are buying. That is underrated.
Star rating summary
Freshness ⭐⭐⭐☆☆ (3/5) | Richness ⭐⭐☆☆☆ (2/5) | Scalability ⭐⭐⭐⭐☆ (4/5) | Pricing ⭐⭐⭐⭐☆ (4/5) | Dev ⭐⭐⭐⭐☆ (4/5) | Stability ⭐⭐⭐⭐⭐ (5/5) | AI ⭐☆☆☆☆ (1/5)
9. Clay
What it does
Clay is orchestration. It is not one enrichment API. It is a way to glue several together.
How I scored it
I scored richness and dev-friendliness 4/5 because Clay gives technical teams a lot of workflow flexibility. I scored pricing 2/5 because the true cost depends on both Clay and the providers you connect. That is the core tradeoff. AI readiness is 2/5 because Clay is conceptually very useful in AI-assisted workflows, but I did not find the same kind of public machine-readable AI-doc surface as NinjaPear.
Pricing
Depends on workflow credits and provider spend.
AI dimension
- AI Skill: No clear public evidence found
- MCP or agent path: No clear public evidence found
- Markdown docs: No clear public evidence found
llms.txt: No clear public evidence found- OpenAPI spec: No clear public evidence found
What I like
Very flexible. Good for waterfalls, branching, and ops workflows.
What will annoy you
Budget leakage if you do not watch it carefully.
I recommend you seriously consider replacing ZoomInfo with Clay ... but only after a pilot run, to validate Clay’s coverage and accuracy.
That is the right mentality with Clay. Pilot first. Model cost carefully.
Best for
GTM engineers who need orchestration.
Star rating summary
Freshness ⭐⭐⭐⭐☆ (4/5) | Richness ⭐⭐⭐⭐☆ (4/5) | Scalability ⭐⭐⭐⭐☆ (4/5) | Pricing ⭐⭐☆☆☆ (2/5) | Dev ⭐⭐⭐⭐☆ (4/5) | Stability ⭐⭐⭐⭐☆ (4/5) | AI ⭐⭐☆☆☆ (2/5)
10. Crunchbase
What it does
Crunchbase is company and funding data. Useful, but not broad contact enrichment.
How I scored it
I scored richness 3/5 because the company and funding layer is useful, but narrower than broader intelligence products. I scored dev-friendliness 4/5 because the API story is real and the company-data use cases are clear. AI readiness stays 1/5 because I found no clear public AI-doc evidence.
Pricing
Mixed.
AI dimension
- AI Skill: No clear public evidence found
- MCP or agent path: No clear public evidence found
- Markdown docs: No clear public evidence found
llms.txt: No clear public evidence found- OpenAPI spec: No clear public evidence found
What I like
Funding and company metadata remain useful for segmentation and market mapping.
What will annoy you
Weak person and contact story.
Best for
Company-level enrichment and funding-aware workflows.
User signal
Crunchbase still matters when the company object matters more than the contact object.
Star rating summary
Freshness ⭐⭐⭐☆☆ (3/5) | Richness ⭐⭐⭐☆☆ (3/5) | Scalability ⭐⭐⭐⭐☆ (4/5) | Pricing ⭐⭐⭐☆☆ (3/5) | Dev ⭐⭐⭐⭐☆ (4/5) | Stability ⭐⭐⭐⭐⭐ (5/5) | AI ⭐☆☆☆☆ (1/5)
11. Cognism
What it does
Cognism is premium B2B sales data, especially where phone data matters.
How I scored it
I scored richness 4/5 because the phone and contact angle is a real strength. Pricing is 2/5 because even though public CRM enrichment content references pricing from ~$12,000 annually, the actual motion is still contract-led. Dev-friendliness is 2/5 because it does not feel like a builder-first product in public.
Pricing
Public CRM enrichment content says pricing starts around $12,000 annually including 25,000 credits.
AI dimension
- AI Skill: No clear public evidence found
- MCP or agent path: No clear public evidence found
- Markdown docs: No clear public evidence found
llms.txt: No clear public evidence found- OpenAPI spec: No clear public evidence found
What I like
Phone coverage is stronger than a lot of mid-market vendors.
What will annoy you
Not a builder-first feel.
Best for
Teams where phone coverage matters a lot.
User signal
Cognism usually enters the conversation when teams care about higher-end sales data rather than cheap API experimentation.
Star rating summary
Freshness ⭐⭐⭐☆☆ (3/5) | Richness ⭐⭐⭐⭐☆ (4/5) | Scalability ⭐⭐⭐⭐☆ (4/5) | Pricing ⭐⭐☆☆☆ (2/5) | Dev ⭐⭐☆☆☆ (2/5) | Stability ⭐⭐⭐⭐☆ (4/5) | AI ⭐☆☆☆☆ (1/5)
12. RocketReach
What it does
RocketReach is contact-finding API territory. Email. Phone. Straight-line use cases.
How I scored it
I scored richness 3/5 because the contact layer is useful but not especially broad. I scored pricing 3/5 because the public site exposes plans and mentions API limits, but the real API economics still drift into contract language. Stability is 4/5 because it is a familiar product with a long operating history.
Pricing
Public pricing shows plans with higher API limits starting around $6k annually, but API-only economics are still not especially crisp.
AI dimension
- AI Skill: No clear public evidence found
- MCP or agent path: No clear public evidence found
- Markdown docs: No clear public evidence found
llms.txt: No clear public evidence found- OpenAPI spec: No clear public evidence found
What I like
Familiar and usually serviceable.
What will annoy you
It rarely wins on workflow depth or pricing clarity.
Best for
Basic contact enrichment.
User signal
RocketReach is often the answer when teams want something known and adequate, not especially opinionated.
Star rating summary
Freshness ⭐⭐⭐☆☆ (3/5) | Richness ⭐⭐⭐☆☆ (3/5) | Scalability ⭐⭐⭐⭐☆ (4/5) | Pricing ⭐⭐⭐☆☆ (3/5) | Dev ⭐⭐⭐☆☆ (3/5) | Stability ⭐⭐⭐⭐☆ (4/5) | AI ⭐☆☆☆☆ (1/5)
13. UpLead
What it does
UpLead gives you verified contacts and company data in a cleaner mid-market package.
How I scored it
I scored most dimensions at 3/5 because UpLead is competent across the board without being especially differentiated. Stability gets 4/5 because it remains a credible mid-market option. AI readiness stays 1/5 because I found no clear public evidence beyond standard docs.
Pricing
Public plans exist and the site says API access is included by plan. Real economics still depend on plan level.
AI dimension
- AI Skill: No clear public evidence found
- MCP or agent path: No clear public evidence found
- Markdown docs: No clear public evidence found
llms.txt: No clear public evidence found- OpenAPI spec: No clear public evidence found
What I like
Less enterprise theater than ZoomInfo.
What will annoy you
Still feels more sales tool than developer platform.
Best for
Mid-market teams that want verified contacts without ZoomInfo pricing gravity.
User signal
UpLead tends to come up when buyers want something cleaner than the enterprise incumbents and less ops-heavy than Clay.
Star rating summary
Freshness ⭐⭐⭐☆☆ (3/5) | Richness ⭐⭐⭐☆☆ (3/5) | Scalability ⭐⭐⭐☆☆ (3/5) | Pricing ⭐⭐⭐☆☆ (3/5) | Dev ⭐⭐⭐☆☆ (3/5) | Stability ⭐⭐⭐⭐☆ (4/5) | AI ⭐☆☆☆☆ (1/5)
14. Dropcontact
What it does
Dropcontact is email enrichment with pay-for-success pricing and privacy positioning.
How I scored it
I scored pricing 4/5 because the public pay-on-success model is straightforward and rational. I scored richness 2/5 because this is a narrower email enrichment product, not a broader account-intelligence layer. Stability is 4/5 because the product knows its lane.
Pricing
You pay when an email is found or verified.
AI dimension
- AI Skill: No clear public evidence found
- MCP or agent path: No clear public evidence found
- Markdown docs: No clear public evidence found
llms.txt: No clear public evidence found- OpenAPI spec: No clear public evidence found
What I like
Paying for success is rational.
What will annoy you
Scope is narrow.
Best for
Privacy-conscious email enrichment.
User signal
Dropcontact is appealing when buyers are tired of paying for misses.
Star rating summary
Freshness ⭐⭐⭐☆☆ (3/5) | Richness ⭐⭐☆☆☆ (2/5) | Scalability ⭐⭐⭐☆☆ (3/5) | Pricing ⭐⭐⭐⭐☆ (4/5) | Dev ⭐⭐⭐☆☆ (3/5) | Stability ⭐⭐⭐⭐☆ (4/5) | AI ⭐☆☆☆☆ (1/5)
15. Clearout
What it does
Clearout is email finder, verifier, and narrow enrichment.
How I scored it
I scored pricing 4/5 because public pricing is easy to find and the rollover policy is unusually buyer-friendly. I scored richness 2/5 because it is still a narrow product relative to broader enrichment APIs. Stability is 4/5 because the economics are transparent and the scope is clear.
Pricing
Starter 3,000 credits at $16/mo annual or $19.5 monthly. Pro 10K credits at $32/mo annual or $40 monthly. Credits roll over.
AI dimension
- AI Skill: No clear public evidence found
- MCP or agent path: No clear public evidence found
- Markdown docs: No clear public evidence found
llms.txt: No clear public evidence found- OpenAPI spec: No clear public evidence found
What I like
Clear economics.
What will annoy you
Narrower scope than people think.
Best for
Verifier-heavy email workflows.
User signal
Clearout is one of the easier products here to reason about financially. That matters more than people admit.
Star rating summary
Freshness ⭐⭐⭐☆☆ (3/5) | Richness ⭐⭐☆☆☆ (2/5) | Scalability ⭐⭐⭐☆☆ (3/5) | Pricing ⭐⭐⭐⭐☆ (4/5) | Dev ⭐⭐⭐☆☆ (3/5) | Stability ⭐⭐⭐⭐☆ (4/5) | AI ⭐☆☆☆☆ (1/5)
16. Snov.io
What it does
Budget outbound platform with enrichment features.
How I scored it
I scored pricing 4/5 because public entry pricing is easy to find and low enough for small teams to test. I scored dev-friendliness 2/5 because while API access exists, the product still feels like an outbound suite first and infra second. AI readiness stays 1/5 because I found no public evidence of agent-specific docs.
Pricing
Around $39/mo publicly.
AI dimension
- AI Skill: No clear public evidence found
- MCP or agent path: No clear public evidence found
- Markdown docs: No clear public evidence found
llms.txt: No clear public evidence found- OpenAPI spec: No clear public evidence found
What I like
Cheap to try.
What will annoy you
Not serious data infrastructure.
Best for
Small outbound teams with small budgets.
User signal
Snov.io tends to win small-budget experiments, not serious platform decisions.
Star rating summary
Freshness ⭐⭐☆☆☆ (2/5) | Richness ⭐⭐☆☆☆ (2/5) | Scalability ⭐⭐⭐☆☆ (3/5) | Pricing ⭐⭐⭐⭐☆ (4/5) | Dev ⭐⭐☆☆☆ (2/5) | Stability ⭐⭐⭐☆☆ (3/5) | AI ⭐☆☆☆☆ (1/5)
17. Lusha
What it does
Lusha is contact data for SDR teams.
How I scored it
I scored richness 3/5 because the contact layer is useful for rep workflows. I scored pricing and dev-friendliness 2/5 because the API is not the center of gravity and the product story is more sales-tool than developer platform.
Pricing
Public plans exist. API is not the center of gravity.
AI dimension
- AI Skill: No clear public evidence found
- MCP or agent path: No clear public evidence found
- Markdown docs: No clear public evidence found
llms.txt: No clear public evidence found- OpenAPI spec: No clear public evidence found
What I like
Simple SDR product story.
What will annoy you
Not very interesting for flexible product workflows.
Best for
SDR teams that want speed over elegance.
User signal
Lusha is easy to explain internally. That is a real buying advantage, even if it is not the most flexible API product.
Star rating summary
Freshness ⭐⭐☆☆☆ (2/5) | Richness ⭐⭐⭐☆☆ (3/5) | Scalability ⭐⭐⭐☆☆ (3/5) | Pricing ⭐⭐☆☆☆ (2/5) | Dev ⭐⭐☆☆☆ (2/5) | Stability ⭐⭐⭐⭐☆ (4/5) | AI ⭐☆☆☆☆ (1/5)
18. ContactOut
What it does
ContactOut is people-first enrichment with recruiter DNA.
How I scored it
I scored richness 2/5 because the company story is weak, but the people and contact use case is clear. Pricing and dev-friendliness sit at 3/5 because public pricing exists and API access exists, but the platform is still more recruiter/contact oriented than broad enrichment infra.
Pricing
$99/mo for email. $199/mo for email + phone.
AI dimension
- AI Skill: No clear public evidence found
- MCP or agent path: No clear public evidence found
- Markdown docs: No clear public evidence found
llms.txt: No clear public evidence found- OpenAPI spec: No clear public evidence found
What I like
Useful if your problem is people and contact info.
What will annoy you
Weak company story.
Best for
Recruiting and sourcing.
User signal
ContactOut makes more sense when the person object matters more than the account object.
Star rating summary
Freshness ⭐⭐⭐☆☆ (3/5) | Richness ⭐⭐☆☆☆ (2/5) | Scalability ⭐⭐⭐☆☆ (3/5) | Pricing ⭐⭐⭐☆☆ (3/5) | Dev ⭐⭐⭐☆☆ (3/5) | Stability ⭐⭐⭐⭐☆ (4/5) | AI ⭐☆☆☆☆ (1/5)
19. LeadMagic
What it does
LeadMagic is API-first enough to be interesting if you think in waterfalls.
How I scored it
I scored pricing and dev-friendliness 4/5 because the pay-per-result framing and API orientation make it easier to reason about than many sales-led tools. I scored AI readiness 2/5 because there is at least some public AI-agent positioning, but not the stronger machine-readable evidence I looked for elsewhere. Stability is 3/5 because the brand is still less proven than larger incumbents.
Pricing
Starts at $49/mo with pay-per-result positioning.
AI dimension
- AI Skill: Some public AI-agent positioning
- MCP or agent path: No clear public evidence found
- Markdown docs: No clear public evidence found
llms.txt: No clear public evidence found- OpenAPI spec: No clear public evidence found
What I like
Interesting alternative to bigger incumbents if you care about waterfall economics.
What will annoy you
Brand trust is lower.
Best for
Waterfall-heavy GTM engineering.
User signal
LeadMagic is the sort of vendor technical buyers try when they are tired of paying for broad seats they do not need.
Star rating summary
Freshness ⭐⭐⭐☆☆ (3/5) | Richness ⭐⭐⭐☆☆ (3/5) | Scalability ⭐⭐⭐⭐☆ (4/5) | Pricing ⭐⭐⭐⭐☆ (4/5) | Dev ⭐⭐⭐⭐☆ (4/5) | Stability ⭐⭐⭐☆☆ (3/5) | AI ⭐⭐☆☆☆ (2/5)
20. Kaspr
What it does
Kaspr is LinkedIn-URL-driven contact enrichment.
How I scored it
I scored richness 2/5 because it is useful but narrow. Pricing and scalability are 3/5 because public plans exist and API access starts at Starter, but it is still not the primary product story. Dev-friendliness is 2/5 because the API feels secondary.
Pricing
Starts at €45/mo. API from Starter.
AI dimension
- AI Skill: No clear public evidence found
- MCP or agent path: No clear public evidence found
- Markdown docs: No clear public evidence found
llms.txt: No clear public evidence found- OpenAPI spec: No clear public evidence found
What I like
Simple fit if LinkedIn URL is your starting key.
What will annoy you
Credit logic can get annoying. Export credits apply too.
Best for
Known-profile enrichment.
User signal
Kaspr is practical when your workflow already starts from known profiles, less compelling as a general data layer.
Star rating summary
Freshness ⭐⭐☆☆☆ (2/5) | Richness ⭐⭐☆☆☆ (2/5) | Scalability ⭐⭐⭐☆☆ (3/5) | Pricing ⭐⭐⭐☆☆ (3/5) | Dev ⭐⭐☆☆☆ (2/5) | Stability ⭐⭐⭐☆☆ (3/5) | AI ⭐☆☆☆☆ (1/5)
21. Prospeo
What it does
Prospeo is a lean, cheaper enrichment option for emails, phones, and simple lookups.
How I scored it
I scored pricing 4/5 because the public credit model is simple. Richness is 2/5 because breadth is limited. Dev-friendliness and stability sit at 3/5 because the product is transparent but clearly aimed at smaller workflows.
Pricing
Public API pricing says 1 credit per enrichment request.
AI dimension
- AI Skill: No clear public evidence found
- MCP or agent path: No clear public evidence found
- Markdown docs: No clear public evidence found
llms.txt: No clear public evidence found- OpenAPI spec: No clear public evidence found
What I like
Transparent. Cheap enough.
What will annoy you
Limited breadth.
Best for
Small teams optimizing for cost.
User signal
Prospeo makes the most sense when cost discipline matters more than breadth.
Star rating summary
Freshness ⭐⭐⭐☆☆ (3/5) | Richness ⭐⭐☆☆☆ (2/5) | Scalability ⭐⭐⭐☆☆ (3/5) | Pricing ⭐⭐⭐⭐☆ (4/5) | Dev ⭐⭐⭐☆☆ (3/5) | Stability ⭐⭐⭐☆☆ (3/5) | AI ⭐☆☆☆☆ (1/5)
22. Adapt.io
What it does
Adapt.io is an older B2B lead platform that still shows up in evaluations.
How I scored it
I scored most dimensions between 2/5 and 3/5 because it is serviceable, public enough to understand, and less differentiated than more active products in the category. AI readiness stays 1/5 because I found no clear public evidence of agent-oriented docs.
Pricing
Free, $49, and $99 public tiers.
AI dimension
- AI Skill: No clear public evidence found
- MCP or agent path: No clear public evidence found
- Markdown docs: No clear public evidence found
llms.txt: No clear public evidence found- OpenAPI spec: No clear public evidence found
What I like
Easy enough to understand.
What will annoy you
This is not where the category feels active.
Best for
Teams that already know the tool.
User signal
Adapt is still in evaluation sets mostly because it has been around for a while, not because the category feels centered there.
Star rating summary
Freshness ⭐⭐☆☆☆ (2/5) | Richness ⭐⭐☆☆☆ (2/5) | Scalability ⭐⭐⭐☆☆ (3/5) | Pricing ⭐⭐⭐☆☆ (3/5) | Dev ⭐⭐☆☆☆ (2/5) | Stability ⭐⭐⭐☆☆ (3/5) | AI ⭐☆☆☆☆ (1/5)
23. Seamless.AI
What it does
Seamless.AI is a high-awareness outbound data vendor.
How I scored it
I scored awareness-driven richness 3/5 because the outbound use case is obvious, but pricing, dev-friendliness, and stability all land lower because public API evaluation remains fuzzy and buyer skepticism is part of the market conversation. AI readiness is 1/5 because I found no clear public evidence.
Pricing
Free trial. Real pricing gets sales-led.
AI dimension
- AI Skill: No clear public evidence found
- MCP or agent path: No clear public evidence found
- Markdown docs: No clear public evidence found
llms.txt: No clear public evidence found- OpenAPI spec: No clear public evidence found
What I like
Awareness matters. Some teams buy the known brand.
What will annoy you
Trust issues and vague pricing.
Best for
Teams that want awareness and broad outbound utility.
User signal
This is one of the vendors where brand visibility outruns product trust in a lot of buyer conversations.
Star rating summary
Freshness ⭐⭐☆☆☆ (2/5) | Richness ⭐⭐⭐☆☆ (3/5) | Scalability ⭐⭐⭐☆☆ (3/5) | Pricing ⭐⭐☆☆☆ (2/5) | Dev ⭐⭐☆☆☆ (2/5) | Stability ⭐⭐☆☆☆ (2/5) | AI ⭐☆☆☆☆ (1/5)
24. Datagma
What it does
Datagma is a lower-visibility API-first-ish alternative.
How I scored it
I scored pricing 4/5 because public entry pricing is visible. Richness is 2/5 because the proof footprint is smaller and the product looks narrower than higher-ranked vendors. Dev-friendliness and stability sit at 3/5 because it is testable without too much friction.
Pricing
Starts at $39/mo billed yearly.
AI dimension
- AI Skill: No clear public evidence found
- MCP or agent path: No clear public evidence found
- Markdown docs: No clear public evidence found
llms.txt: No clear public evidence found- OpenAPI spec: No clear public evidence found
What I like
Cheap enough to test. Worth a look if you want alternatives.
What will annoy you
Smaller proof footprint.
Best for
Buyers who want a lower-cost API-first option.
User signal
Datagma is the kind of vendor technical buyers try when they want to get outside the loud incumbent set.
Star rating summary
Freshness ⭐⭐⭐☆☆ (3/5) | Richness ⭐⭐☆☆☆ (2/5) | Scalability ⭐⭐⭐☆☆ (3/5) | Pricing ⭐⭐⭐⭐☆ (4/5) | Dev ⭐⭐⭐☆☆ (3/5) | Stability ⭐⭐⭐☆☆ (3/5) | AI ⭐☆☆☆☆ (1/5)
25. Coresignal
What it does
Coresignal is closer to workforce and public-web data infrastructure than a clean general enrichment buy.
How I scored it
I scored scalability 4/5 because the API-plus-dataset model works for technical teams building data products. I scored richness 3/5 because workforce and company-web data can be useful, but this is not the cleanest general enrichment fit. Pricing is 3/5 because public API entry pricing starts at $49/mo, but dataset economics can expand quickly. AI readiness is 1/5 because I found no clear public machine-first AI docs layer.
Pricing
API starts at $49/mo. Datasets cost more.
AI dimension
- AI Skill: No clear public evidence found
- MCP or agent path: No clear public evidence found
- Markdown docs: No clear public evidence found
llms.txt: No clear public evidence found- OpenAPI spec: No clear public evidence found
What I like
Useful if you care about workforce or company data layers.
What will annoy you
It is not the cleanest plug-and-play enrichment product.
Like PDL, it also lives near the LinkedIn-derived data conversation. If that matters to your counsel, read this: Is scraping LinkedIn legal in 2026?
Best for
Workforce intelligence and custom data products.
User signal
Coresignal makes the most sense when enrichment is one layer inside a larger data workflow, not the whole buying reason.
Star rating summary
Freshness ⭐⭐⭐☆☆ (3/5) | Richness ⭐⭐⭐☆☆ (3/5) | Scalability ⭐⭐⭐⭐☆ (4/5) | Pricing ⭐⭐⭐☆☆ (3/5) | Dev ⭐⭐⭐⭐☆ (4/5) | Stability ⭐⭐⭐⭐☆ (4/5) | AI ⭐☆☆☆☆ (1/5)
What most buyers miss
Freshness beats field count
Twenty wrong fields are worse than five right ones.
The CRM had one job. Give you context and help you figure out where to focus. Instead it became a dashboard for management.
A bigger field list does not help if the org changed, the exec left, or the company pivoted.
Credits hide real cost
Most pricing spreadsheets are wrong because they model one pass.
Real cost is:
- initial enrichment
- misses
- premium fields
- re-enrichment
- waterfall fallback
- webhook and ops overhead
That is how a cheap API becomes an expensive one.
Workflow fit matters more
A wrong field is worse than a blank field.
Blank fields make your system cautious. Wrong fields make your reps overconfident.
Yeah I run GTME for an 80 person org, got rid of ZI and Lusha. I replaced it with a slack enrichment...
That thread was about tooling replacement, but the point is broader. Use-case mismatch breaks tools quickly.
AI-readiness is now real
This is not a side issue anymore.
If your docs are hard for AI coding agents to consume, implementation gets slower and more brittle. Teams feel that immediately.
My hot takes
- Freshness is the product. Old data with more fields is still old data.
- Opaque pricing is a product flaw. If I need a sales call to find out whether a tool is in budget, evaluation got harder for no good reason.
- Most all-in-one enrichment tools are really prospecting databases with an API attached. That changes how you should buy them.
- A wrong field is worse than a blank field. Blank makes software cautious. Wrong creates bad decisions.
- AI-readiness is not optional anymore. If Claude or Cursor cannot consume your docs, your developer experience is behind.
- Static enrichment is the start. The next question is what changed and why now.
Final picks by use case
If you want the short version:
Best overall data enrichment api
NinjaPear
Because it is pointed at modern workflows: company intelligence, relationship mapping, monitoring, and AI-friendly docs.
Best exact-match generic enrichment API
EnrichmentAPI
Because it is focused, public, and easy to reason about.
Best builder-grade data layer
People Data Labs
Because it still feels like serious infrastructure, assuming you understand the freshness tradeoff and the LinkedIn data conversation.
Best default prospecting stack with enrichment included
Apollo
Because it is still the broad convenience play, even if the API side gets more complex.
Best for HubSpot-heavy routing workflows
Clearbit
If you can tolerate opaque pricing.
Best for email-centric enrichment
Hunter
Simple. Focused. Usually enough.
Best for waterfall orchestration
Clay if you need orchestration.
LeadMagic if you want something more API-centered.
Best for enterprise incumbency
ZoomInfo
If you have budget and patience.
The actual advice is simple: stop asking which data enrichment api has the most fields. Ask which one fits your workflow, refresh cadence, and tolerance for pricing games.
If your real problem is timing, org change, competitor movement, or relationship mapping, generic enrichment is not enough. Start with NinjaPear.
If your problem is simpler, test EnrichmentAPI and People Data Labs next.
And if you want to check your own cost model before you buy anything, use the calculator below. It will save you more money than another vendor call.
Use it to estimate monthly spend, re-enrichment load, cost per successful match, and whether a vendor’s docs are usable in an AI-assisted workflow.
Download now →
TL;DR
This is the full market map. Average score is the sum of the 7 category scores divided by 7.
| Vendor | Avg | Freshness | Richness | Scalability | Pricing | Dev-Friendly | Stability | AI Readiness |
|---|---|---|---|---|---|---|---|---|
| NinjaPear | 4.43/5 | ⭐⭐⭐⭐⭐ 5/5 | ⭐⭐⭐⭐☆ 4/5 | ⭐⭐⭐⭐☆ 4/5 | ⭐⭐⭐⭐☆ 4/5 | ⭐⭐⭐⭐⭐ 5/5 | ⭐⭐⭐⭐☆ 4/5 | ⭐⭐⭐⭐⭐ 5/5 |
| EnrichmentAPI | 3.43/5 | ⭐⭐⭐⭐☆ 4/5 | ⭐⭐⭐⭐☆ 4/5 | ⭐⭐⭐⭐☆ 4/5 | ⭐⭐⭐⭐☆ 4/5 | ⭐⭐⭐⭐☆ 4/5 | ⭐⭐⭐☆☆ 3/5 | ⭐☆☆☆☆ 1/5 |
| People Data Labs | 3.86/5 | ⭐⭐⭐☆☆ 3/5 | ⭐⭐⭐⭐☆ 4/5 | ⭐⭐⭐⭐⭐ 5/5 | ⭐⭐⭐☆☆ 3/5 | ⭐⭐⭐⭐⭐ 5/5 | ⭐⭐⭐⭐⭐ 5/5 | ⭐⭐☆☆☆ 2/5 |
| Apollo | 2.86/5 | ⭐⭐☆☆☆ 2/5 | ⭐⭐⭐⭐☆ 4/5 | ⭐⭐⭐⭐☆ 4/5 | ⭐⭐⭐☆☆ 3/5 | ⭐⭐☆☆☆ 2/5 | ⭐⭐⭐⭐☆ 4/5 | ⭐☆☆☆☆ 1/5 |
| Clearbit | 3.29/5 | ⭐⭐⭐⭐☆ 4/5 | ⭐⭐⭐⭐☆ 4/5 | ⭐⭐⭐⭐☆ 4/5 | ⭐⭐☆☆☆ 2/5 | ⭐⭐⭐☆☆ 3/5 | ⭐⭐⭐⭐⭐ 5/5 | ⭐☆☆☆☆ 1/5 |
| ZoomInfo | 3.14/5 | ⭐⭐⭐☆☆ 3/5 | ⭐⭐⭐⭐⭐ 5/5 | ⭐⭐⭐⭐⭐ 5/5 | ⭐☆☆☆☆ 1/5 | ⭐⭐☆☆☆ 2/5 | ⭐⭐⭐⭐⭐ 5/5 | ⭐☆☆☆☆ 1/5 |
| FullContact | 3.29/5 | ⭐⭐⭐☆☆ 3/5 | ⭐⭐⭐⭐☆ 4/5 | ⭐⭐⭐⭐☆ 4/5 | ⭐⭐☆☆☆ 2/5 | ⭐⭐⭐⭐☆ 4/5 | ⭐⭐⭐⭐☆ 4/5 | ⭐⭐☆☆☆ 2/5 |
| Hunter | 3.29/5 | ⭐⭐⭐☆☆ 3/5 | ⭐⭐☆☆☆ 2/5 | ⭐⭐⭐⭐☆ 4/5 | ⭐⭐⭐⭐☆ 4/5 | ⭐⭐⭐⭐☆ 4/5 | ⭐⭐⭐⭐⭐ 5/5 | ⭐☆☆☆☆ 1/5 |
| Clay | 3.43/5 | ⭐⭐⭐⭐☆ 4/5 | ⭐⭐⭐⭐☆ 4/5 | ⭐⭐⭐⭐☆ 4/5 | ⭐⭐☆☆☆ 2/5 | ⭐⭐⭐⭐☆ 4/5 | ⭐⭐⭐⭐☆ 4/5 | ⭐⭐☆☆☆ 2/5 |
| Crunchbase | 3.29/5 | ⭐⭐⭐☆☆ 3/5 | ⭐⭐⭐☆☆ 3/5 | ⭐⭐⭐⭐☆ 4/5 | ⭐⭐⭐☆☆ 3/5 | ⭐⭐⭐⭐☆ 4/5 | ⭐⭐⭐⭐⭐ 5/5 | ⭐☆☆☆☆ 1/5 |
| Cognism | 2.86/5 | ⭐⭐⭐☆☆ 3/5 | ⭐⭐⭐⭐☆ 4/5 | ⭐⭐⭐⭐☆ 4/5 | ⭐⭐☆☆☆ 2/5 | ⭐⭐☆☆☆ 2/5 | ⭐⭐⭐⭐☆ 4/5 | ⭐☆☆☆☆ 1/5 |
| RocketReach | 3.00/5 | ⭐⭐⭐☆☆ 3/5 | ⭐⭐⭐☆☆ 3/5 | ⭐⭐⭐⭐☆ 4/5 | ⭐⭐⭐☆☆ 3/5 | ⭐⭐⭐☆☆ 3/5 | ⭐⭐⭐⭐☆ 4/5 | ⭐☆☆☆☆ 1/5 |
| UpLead | 2.86/5 | ⭐⭐⭐☆☆ 3/5 | ⭐⭐⭐☆☆ 3/5 | ⭐⭐⭐☆☆ 3/5 | ⭐⭐⭐☆☆ 3/5 | ⭐⭐⭐☆☆ 3/5 | ⭐⭐⭐⭐☆ 4/5 | ⭐☆☆☆☆ 1/5 |
| Dropcontact | 2.86/5 | ⭐⭐⭐☆☆ 3/5 | ⭐⭐☆☆☆ 2/5 | ⭐⭐⭐☆☆ 3/5 | ⭐⭐⭐⭐☆ 4/5 | ⭐⭐⭐☆☆ 3/5 | ⭐⭐⭐⭐☆ 4/5 | ⭐☆☆☆☆ 1/5 |
| Clearout | 2.86/5 | ⭐⭐⭐☆☆ 3/5 | ⭐⭐☆☆☆ 2/5 | ⭐⭐⭐☆☆ 3/5 | ⭐⭐⭐⭐☆ 4/5 | ⭐⭐⭐☆☆ 3/5 | ⭐⭐⭐⭐☆ 4/5 | ⭐☆☆☆☆ 1/5 |
| Snov.io | 2.43/5 | ⭐⭐☆☆☆ 2/5 | ⭐⭐☆☆☆ 2/5 | ⭐⭐⭐☆☆ 3/5 | ⭐⭐⭐⭐☆ 4/5 | ⭐⭐☆☆☆ 2/5 | ⭐⭐⭐☆☆ 3/5 | ⭐☆☆☆☆ 1/5 |
| Lusha | 2.43/5 | ⭐⭐☆☆☆ 2/5 | ⭐⭐⭐☆☆ 3/5 | ⭐⭐⭐☆☆ 3/5 | ⭐⭐☆☆☆ 2/5 | ⭐⭐☆☆☆ 2/5 | ⭐⭐⭐⭐☆ 4/5 | ⭐☆☆☆☆ 1/5 |
| ContactOut | 2.71/5 | ⭐⭐⭐☆☆ 3/5 | ⭐⭐☆☆☆ 2/5 | ⭐⭐⭐☆☆ 3/5 | ⭐⭐⭐☆☆ 3/5 | ⭐⭐⭐☆☆ 3/5 | ⭐⭐⭐⭐☆ 4/5 | ⭐☆☆☆☆ 1/5 |
| LeadMagic | 3.29/5 | ⭐⭐⭐☆☆ 3/5 | ⭐⭐⭐☆☆ 3/5 | ⭐⭐⭐⭐☆ 4/5 | ⭐⭐⭐⭐☆ 4/5 | ⭐⭐⭐⭐☆ 4/5 | ⭐⭐⭐☆☆ 3/5 | ⭐⭐☆☆☆ 2/5 |
| Kaspr | 2.29/5 | ⭐⭐☆☆☆ 2/5 | ⭐⭐☆☆☆ 2/5 | ⭐⭐⭐☆☆ 3/5 | ⭐⭐⭐☆☆ 3/5 | ⭐⭐☆☆☆ 2/5 | ⭐⭐⭐☆☆ 3/5 | ⭐☆☆☆☆ 1/5 |
| Prospeo | 2.71/5 | ⭐⭐⭐☆☆ 3/5 | ⭐⭐☆☆☆ 2/5 | ⭐⭐⭐☆☆ 3/5 | ⭐⭐⭐⭐☆ 4/5 | ⭐⭐⭐☆☆ 3/5 | ⭐⭐⭐☆☆ 3/5 | ⭐☆☆☆☆ 1/5 |
| Adapt.io | 2.29/5 | ⭐⭐☆☆☆ 2/5 | ⭐⭐☆☆☆ 2/5 | ⭐⭐⭐☆☆ 3/5 | ⭐⭐⭐☆☆ 3/5 | ⭐⭐☆☆☆ 2/5 | ⭐⭐⭐☆☆ 3/5 | ⭐☆☆☆☆ 1/5 |
| Seamless.AI | 2.14/5 | ⭐⭐☆☆☆ 2/5 | ⭐⭐⭐☆☆ 3/5 | ⭐⭐⭐☆☆ 3/5 | ⭐⭐☆☆☆ 2/5 | ⭐⭐☆☆☆ 2/5 | ⭐⭐☆☆☆ 2/5 | ⭐☆☆☆☆ 1/5 |
| Datagma | 2.71/5 | ⭐⭐⭐☆☆ 3/5 | ⭐⭐☆☆☆ 2/5 | ⭐⭐⭐☆☆ 3/5 | ⭐⭐⭐⭐☆ 4/5 | ⭐⭐⭐☆☆ 3/5 | ⭐⭐⭐☆☆ 3/5 | ⭐☆☆☆☆ 1/5 |
| Coresignal | 3.14/5 | ⭐⭐⭐☆☆ 3/5 | ⭐⭐⭐☆☆ 3/5 | ⭐⭐⭐⭐☆ 4/5 | ⭐⭐⭐☆☆ 3/5 | ⭐⭐⭐⭐☆ 4/5 | ⭐⭐⭐⭐☆ 4/5 | ⭐☆☆☆☆ 1/5 |
That is the board.
If you want the most interesting thing to evaluate first, start with NinjaPear.
If you want a cleaner generic enrichment product, test EnrichmentAPI.
If you want serious builder infrastructure, test People Data Labs.
If you want convenience and can live with some complexity, Apollo is still there.
