I was researching the best company data API for my own work. I decided to trawl through Reddit, and then share what I found so no one else has to do the same again. I read 11 Reddit threads and 181 comments about company data APIs. Half of the recommendations are vendors pretending to be customers. Almost nobody posts real responses. What follows is what survived after I removed obvious shills, separated company-data from contact-data noise, and tested one API myself.
The short answer: Reddit does not have a best company data API. It has a best API for a job. For agents and MCP, that API is NinjaPear. The threads are useful in finding fault lines instead of a single winner.
TLDR: The shortlist at a glance
| Provider | Rating | Best for | Watch out |
|---|---|---|---|
| NinjaPear | ★★★★ 4.29/5 | Agents, MCP, live company retrieval | Weak industry coverage, Stripe specialty bug |
| People Data Labs | ★★★☆ 3.67/5 | Bulk company and people graph | Monthly refresh, basic filters |
| Coresignal | ★★★☆ 3.79/5 | Company and job data freshness | Built for data teams, not agents |
| Crustdata | ★★★☆ 3.89/5 | Real-time company signals | No cached profile, coverage varies |
| Apollo | ★★★☆ 3.63/5 | Cheap CRM enrichment | Not API-first, daily search cap |
| Clearbit, now HubSpot Breeze | ★★★☆ 3.69/5 | Easy company and person data | Enterprise pricing, HubSpot packaging |
| CompanyEnrich | ★★★☆ 3.69/5 | Free tier and budget | Founder-run benchmark, limited agent evidence |
| Bright Data | ★★★ 3.37/5 | Raw scraping infrastructure | Monthly refresh, not a clean company API |
| OpenCorporates | ★★★★ 4.07/5 | Official registries and KYB | Registry-dependent freshness, data model work |
| Grata | ★★★☆ 3.69/5 | Private company research | Contact sales, US-focused |
Start with NinjaPear if you are building an agent or an MCP tool. The rest of the list is for the jobs NinjaPear does not fit: bulk company and people data, real-time signals, cheap CRM enrichment, registries and private company research.
What Reddit actually says
I read 11 threads with 181 comments on r/AI_Agents, r/SaaS, r/CRM, r/gtmengineering, r/mcp, r/SideProject, r/n8n, r/B2BSaaS and r/datasets. Threads were posted between June 2024 and October 2026.
The first thing you will notice is that threads are not really about company data APIs. They are about contact data. Emails, phone numbers and job titles, then a vendor account recommends a contact database. The company record is just a side effect. I separated out the comments that were actually about company records, firmographics, headcounts, industry codes and registries.
The second thing you will notice is the shills. Vendors create a question, answer it from an unaffiliated account. It is obvious when you read a few threads: new account, perfect recommendation, link, no criticism. I excluded recommendations that seemed like vendor accounts and kept ones with trade-offs named out. That is why this list is shorter than the threads.
The third thing you will notice is that useful comments are not top comments. The top comment is usually a joke or a vendor. The useful comment is a reply from someone who has actually used the API and hit a limit. I read replies, not just top-level comments.
How I scored
Each vendor gets a score out of 5 in seven attributes: data quality, freshness, legal compliance, coverage, value for money, agent readiness and ease of use. The overall score is the average. This is an editorial score based on linked Reddit comments and public docs, not a user survey. A vendor that does not have a per-record price published cannot score above 3.5 in value. A vendor without an agent path cannot score above 3.0 in agent readiness.
| Provider | Data | Freshness | Legal | Coverage | Value | Agent | Ease | Overall |
|---|---|---|---|---|---|---|---|---|
| NinjaPear | 3.9 | 4.5 | 4.8 | 3.8 | 4.2 | 4.8 | 4.0 | 4.29 |
| People Data Labs | 4.0 | 2.8 | 4.3 | 4.7 | 3.5 | 3.2 | 3.2 | 3.67 |
| Coresignal | 4.3 | 4.5 | 4.2 | 4.5 | 3.2 | 2.8 | 3.0 | 3.79 |
| Crustdata | 4.0 | 4.8 | 3.8 | 3.8 | 3.0 | 4.0 | 3.8 | 3.89 |
| Apollo | 3.4 | 3.2 | 3.5 | 4.5 | 4.3 | 2.5 | 4.0 | 3.63 |
| Clearbit, now HubSpot Breeze | 4.0 | 3.5 | 4.2 | 3.8 | 2.8 | 3.0 | 4.5 | 3.69 |
| CompanyEnrich | 3.8 | 3.5 | 4.0 | 3.2 | 4.5 | 3.0 | 3.8 | 3.69 |
| Bright Data | 3.8 | 3.0 | 3.8 | 3.8 | 3.5 | 3.2 | 2.5 | 3.37 |
| OpenCorporates | 4.5 | 3.5 | 4.8 | 4.7 | 4.0 | 3.5 | 3.5 | 4.07 |
| Grata | 4.0 | 3.8 | 4.2 | 3.8 | 3.0 | 3.5 | 3.5 | 3.69 |
The shortlist, by use case
NinjaPear - ★★★★ 4.29/5
| Best for | Watch out | Price |
|---|---|---|
| Agents and MCP | Weak industry coverage, Stripe specialty bug | $0.036 base, $0.06 with headcount at Growth |
Start here if you are building an agent or an MCP tool. NinjaPear is API-first and MCP-native, with a company details call and an MCP tool called ninjapear_get_company_details. It is the only provider in this piece that I actually tested.
The test is in the next section. Long story short: 4,502,144 company records, great description and headcount coverage, poor industry coverage, real specialty contamination bug on Stripe. If you need an agent to look up a company by domain and return a profile with executives, headcount, funding and customer relationships, NinjaPear is for you. If you need a clean industry code for every SMB, it is not.
Coresignal - ★★★☆ 3.79/5
| Best for | Watch out | Price |
|---|---|---|
| Company and job data freshness | Data-team tooling, not agent-first | Not published |
Coresignal comes up when the complaint is staleness. One r/SaaS commenter compared it directly with PDL:
"People Data Labs (PDL) one of the standard names in the industry. Their APIs are pretty solid for high volume needs. I'll say they fall short in terms of freshness as they update only monthly. The search filters are pretty basic compared to other providers. Coresignal - Similar to PDL but it has more datapoints and more coverage of data. They have more frequent refresh cadences for some basic datapoints like current job title."
Another r/SaaS commenter said they trialed both and chose Coresignal:
"Coresignal and People data labs APIs are both solid, I've trialed both of them, but chose Coresignal because they have more detailed data in general, with multiple sources that are integrated, and their data was way fresher. Also, they have jobs data, and I wanted to find companies that are hiring a lot and expanding."
A Reddit write-up, not an independent test, puts Coresignal at 75M+ company profiles with real-time updates. Treat that number as a claim, not a measurement. Read the r/B2BSales write-up.
The trade-off is in the same thread: Coresignal feels like it was built for data teams instead of agent workflows. If you want a clean API that an LLM can call, this is not the first one to try. If you want a large company dataset with jobs data and have a data engineer, it is.
People Data Labs - ★★★☆ 3.67/5
| Best for | Watch out | Price |
|---|---|---|
| Bulk company and people graph | Monthly refresh, basic filters | Not published |
PDL is the default answer when the requirement is scale. One r/AI_Agents post put the trade-off plainly:
"PDL has good coverage but the monthly batch refresh is a problem for anything real time. Coresignal is solid for company data but feels more built for data teams than agent workflows."
A Reddit write-up puts PDL at 70M+ company profiles and 3B+ person records, updated monthly. Again, that is a Reddit write-up, not an independent test. Read the r/B2BSales write-up.
I wrote a separate guide to PDL's people API that covers the three endpoints, the billing units and the 100-record test.
PDL is the right pick when you need to join people to companies at scale and you can live with a monthly refresh. It is the wrong pick when your agent needs a fresh headcount on every turn. The search filters are also basic compared to newer providers, which matters if your agent needs to filter by role, headcount or industry before it enriches.
Crustdata - ★★★☆ 3.89/5
| Best for | Watch out | Price |
|---|---|---|
| Real-time company signals | No cached profile, coverage varies | Not published |
Crustdata comes up when the requirement is live data and CRM updates. One r/CRM commenter put it in the same breath as ZoomInfo, Cognism and Lusha:
"ZoomInfo, Crustdata, Cognism, Lusha are good CRM enrichment APIs. Crustdata is good if you want live data + auto updates to your CRM. Cognism is great for EU data. ZoomInfo is the 'established' option you asked for but their data is not the best, kinda outdated. Lusha is the cheapest of the options but with it comes a drop in data quality."
A Reddit write-up puts Crustdata at 60M+ company profiles with real-time data but no cached dataset. That means every query is a snapshot, and coverage can vary with what is scrapeable at that moment. Read the r/B2BSales write-up.
Crustdata is a fit for trigger-based outreach: funding, executive moves, hiring. It is a poor fit for a stable company profile that you want to cache and reuse. Lack of a cached dataset is the tradeoff, not a bug.
Apollo - ★★★☆ 3.63/5
| Best for | Watch out | Price |
|---|---|---|
| Cheap CRM enrichment | Not API-first, daily search cap | Not published |
Apollo is the value pick, and also the one with the most caveats. One r/CRM commenter summarized the field:
"Clearbit (now part of HubSpot) - pretty solid for company + person data, easy API. Apollo - good mix of enrichment + contact data. ZoomInfo - very strong data, but expensive and more enterprise. Crunchbase API - good for company-level stuff (funding, size, etc.). People Data Labs - more raw/flexible if you want to build your own logic."
Another commenter warned that Apollo is not API-first:
"Check out Coresignal, Proxycurl, Apollo.io, CompanyEnrich.com, Ocean.io. Apollo's includes a lot of extras but it's not API-first, it's mainly a standalone product, so I'm not sure if it's API is user-friendly."
And an agent builder flagged the rate limit:
"two things to check before you pick one, the rate limit on your actual plan rather than the one on the pricing page, and how much of the record comes back on a single call. the second one is what stops the loop. Apollo - generous per minute but theres a daily cap on the search endpoints, so an agent hits that instead."
Apollo is a great fit for a human-driven CRM cleanup with budget. But it is a terrible fit for an agent that requires searching and enriching thousands of records per day because the search endpoint has a daily cap.
Clearbit, now HubSpot Breeze - ★★★☆ 3.69/5
| Best for | Watch out | Price |
|---|---|---|
| Easy company and person data | Enterprise pricing, HubSpot packaging | HubSpot pricing |
Clearbit is a name that still pops up even though they are now part of HubSpot. The r/CRM quote above calls them "pretty solid for company + person data, easy API." And there it is. It is easy, it is integrated, and it is priced for HubSpot customers. If you are already on HubSpot, then it is the path of least resistance. But if not, the pricing and packaging are harder to justify.
CompanyEnrich - ★★★☆ 3.69/5
| Best for | Watch out | Price |
|---|---|---|
| Free tier and budget | Founder-run benchmark, limited agent evidence | Free tier |
CompanyEnrich shows up in the free-tier threads:
"Coresignal, PeopleDataLabs, companyenrich.com, and thecompaniesapi.com all have generous free tiers that include company details you are looking for."
The only public benchmark is run by the CompanyEnrich founder, so read it with that conflict in mind. On 349 resolved domains, it reports a 67.6% find rate for CompanyEnrich, 61.6% for Apollo, 60.2% for PDL, 53.0% for ContactOut, 50.4% for Coresignal and 50.1% for Crustdata. Average fields per matched profile: 17.9, 15.4, 14.2, 13.7, 13.0 and 11.5. Read the r/gtmengineering benchmark.
It is still useful for a benchmark run by a competitor if you take it as a directional test and not a neutral one. The free tier is the real deal here.
Bright Data - ★★★ 3.37/5
| Best for | Watch out | Price |
|---|---|---|
| Raw scraping infrastructure | Monthly refresh, not a clean company API | Usage-based |
Bright Data is not really a company data API in the same sense as the others. It is scraping infrastructure with a company dataset on top. A Reddit write-up puts it at 58M+ company profiles with a monthly refresh. Read the r/B2BSales write-up.
There is no great Reddit quote to recommend Bright Data for company records. It shows up in threads as infrastructure, not a company API. If you need proxies, scraping and a dataset, then it fits the bill. But if you want a clean company record with a support contract, then it does not.
OpenCorporates - ★★★★ 4.07/5
| Best for | Watch out | Price |
|---|---|---|
| Official registries and KYB | Registry-dependent freshness, data model work | Open data and paid tiers |
Threads are dominated by B2B enrichment vendors. They barely mention official registries. The SERP is different. OpenCorporates showed up in all three SERP pulls I checked. It is the registry play: official company data, open data, good for KYB and compliance. If your use case is to "verify if a company exists and who its officers are," then the Reddit shortlist is not the list you should start with. Start with the registry.
Grata - ★★★☆ 3.69/5
| Best for | Watch out | Price |
|---|---|---|
| Private company research | Contact sales, US-focused | Contact sales |
Grata is the private company research play: search and API for companies that are not public. It appears in the live SERP and not in the Reddit threads. If your use case is "find private companies that match a thesis," Grata is the one the threads miss.
Where Redditors disagree
Redditors disagree on four things. But the disagreements are more useful than recommendations.
Freshness. PDL updates monthly. Coresignal refreshes faster. Crustdata is real-time, but it has no cached profile. NinjaPear is live retrieval, but most calls take 20 to 60 seconds. The right answer depends on whether your agent needs a fresh record every turn or a static profile to cache.
Search. PDL's filters are basic. Coresignal is built for data teams. Apollo has a daily cap on search. It is the agents that loop because the first response did not have the field they needed. One r/mcp commenter called it the stopping-condition problem: the provider should return an explicit "not provided by source" instead of a null that forces the agent to retry.
Price. Apollo is cheap. ZoomInfo is expensive. PDL is sold as a dataset. NinjaPear sells credits. Clay sells seats and credits. The units are not comparable, which is why most buyers do not know if they are getting a good deal. The only way to compare is cost per usable record.
Region. Cognism is the EU pick. ZoomInfo is the US pick. Lusha is cheap but drops in quality. The provider that works in one region can be useless in another.
One more disagreement is about maintenance. A r/gtmengineering commenter put it well:
"what gets overlooked in these threads is the maintenance. sure you can wire up a few APIs to claude and get something working in a weekend, but then you're on the hook for every rate limit, schema change, and auth token rotation. clay bundles all that noise into one bill and one dashboard."
The same thread has the price counterpoint:
"RichAPI charges $2.5 for 1000 linkedin company or profile enrichment, in real-time. Same on Clay is 30x pricier. Same provider, same exact data."
That is the tradeoff in a single thread: you either pay for orchestration, or you pay for the API and own the maintenance. Neither is wrong. But it is wrong to pretend that something is free.
What I tested
NinjaPear is the only provider I tested for this piece. I called the company details endpoint for Stripe and Adyen, and I ran SQL over the company table. The test date is 2026-10-29.
Stripe. A name search returns 5 records. A domain call for stripe.com returns the right top-level fields: 8,500 employees, founded 2010, industry 40201020, headquarters in South San Francisco. The description is right. The specialties are not. The array includes "attacker engineering," "adversary emulation," "threat intelligence" and "security frameworks." Those are another company's specialties. If you build an agent that summarizes a company from this record, it will tell you Stripe does threat intelligence.
Adyen. A domain call for adyen.com returns 13 executives including Pieter van der Does as CEO, 4,771 employees, founded 2006, industry 40201040, headquarters in Amsterdam. This is the clean case. The record looks like a company profile, not a stub.
Coverage. 4,502,144 company records. 4,277,381 have a description (95.0%). 3,965,472 have an employee count (88.1%). 2,616,060 have a founded year (58.1%). 657,230 have an industry code (14.6%). 3,844,914 records have no industry code, or 85.4%.
Industry coverage by size. 1 to 10 employees: 3,232,400 records, 403,627 filled, 12.5%. 11 to 50: 554,386, 73,992, 13.3%. 51 to 200: 132,057, 20,955, 15.9%. 201 to 1,000: 37,519, 8,301, 22.1%. 1,001+: 9,110, 4,383, 48.1%. Unknown: 536,672, 145,973, 27.2%.
Price. The base company details call is 3 credits, or 5 with employee count. At Growth ($299 per month for 25,000 credits, $0.012 per credit), that is $0.036 per base call and $0.06 with headcount. At pay-as-you-go ($50 for 834 credits, $0.06 per credit), it is $0.18 per base call and $0.30 with headcount. Cached calls are free. The API allows 50 requests per minute, and most calls take 20 to 60 seconds.
MCP. The MCP tool is ninjapear_get_company_details, with website and include_employee_count arguments. The REST API is GET /api/v1/company/details. If you are building an agent, the MCP path is the one to test first.
Provenance. NinjaPear does not scrape LinkedIn. Data is compiled from public web sources. That matters if your legal team cares where the data came from.
Who should not use NinjaPear
If you need an industry code for every SMB, this is not the API for you. 85.4% of the database has no industry code, and the smallest companies are the worst: 87.5% of companies with 1 to 10 employees have no code. A filter by industry will remove most of your list before you start.
If you need a static contact CSV with emails and phone numbers, this is not the API for you. NinjaPear is a company intelligence API, not a contact database. The work email coverage is a separate product.
If you need a synchronous user experience, 20 to 60 seconds is too slow. Put the call behind a queue or a cache. If you need a fresh record on every page view, this is not the API for that.
If you need a clean specialties list for every company, test it first. The Stripe record has another company's security specialties. That is a real bug, not a rounding error.
How to pick in an afternoon
Do not pick from this list. Pick from a test. Five checks will tell you more than any listicle, including this one.
- Resolve 10 company names you know to domains. Count the misses. If the provider cannot resolve a name you know, it will not resolve the long tail.
- Pull 10 domains and verify four fields against the company website. Description, headcount, founded year and industry. Count how many are right, not how many are filled.
- Read the specialties and the description. Are they from the right company? The Stripe record shows why this matters.
- Time 10 calls. Record p50 and p95. A 274 ms p50 and a 21,317 ms p50 are different products, even if the resolution rate is the same. The independent 282-company benchmark found a 78x latency range across providers. Read the independent benchmark.
- Run your actual filter. If you need industry, filter by industry and see how many records survive. If you need headcount, filter by headcount. A provider that passes a generic coverage test can still fail your specific query.
The independent benchmark is the best public evidence on resolution and latency. They found that every provider resolves between 94.7% and 100% of domains. So resolution is not the buying signal. Latency is. PDL had a p50 of 274 ms. Apollo had 654 ms. CompanyEnrich had 309 ms. ZoomInfo had 1,132 ms. Exa had 8,143 ms. Parallel had 21,317 ms. If your agent makes 20 calls per task, the difference between 274 ms and 21 seconds is a loop versus a product.
The final verdict is not one winner. It is a shortlist by job. Start with NinjaPear for agents and MCP. Pick PDL for bulk company and people data. Pick Coresignal for fresher company and job data. Pick Crustdata for real-time signals. Pick Apollo for cheap CRM enrichment. Pick CompanyEnrich for free tier. Pick Bright Data for scraping infrastructure. Pick OpenCorporates or Grata when the job is registries or private company research.
The first test to run is the domain resolution test. Take 10 companies that you know, resolve their domains and pull the record. If names are wrong, everything else is noise. If names are right, move on to the four fields. That is it. The whole method. It takes an afternoon.
