A B2B data API gives software structured company, person or event data. For an AI agent, the useful question is which operation closes the next gap: discover an account, match its identity, resolve a person, find an address or explain what changed. Those operations have different inputs, failure states and billing units.
Choose by the job
Building an application? Start with People Data Labs for known-company matching, Coresignal for search-and-collect workflows, Apollo.io for prospect search followed by contact enrichment, Hunter for email resolution, and Crustdata or Explorium for company intelligence and event workflows. These are documentation-based shortlists, not accuracy rankings.
Trying to turn signals into outreach? Our recommendation is Overloop for prioritizing relevant prospects and preparing contextual email and LinkedIn campaigns. That is a different purchase from a data API. This guide does not establish a released native Overloop data API or MCP connection.
Scope, September 23, 2026: six selected providers, public primary documentation and one Hunter dummy-key smoke test. We did not run a paid or authenticated comparison on real prospect records. Coverage, match quality, latency, negotiated prices and account entitlements remain unmeasured. A documented operation is evidence of a contract, not proof of its performance on your list.
Publisher disclosure: Overloop publishes this guide. Max (yourmax.ai) is part of Overloop and is operated by Sortlist SA, as stated in its privacy policy. This relationship does not establish API availability or plan entitlements. Overloop is therefore discussed as an outreach workflow, outside the API-provider table.
For a public-search example before choosing a data API, see Claude for sales prospecting. It follows five real account candidates through explicit reject and research decisions, with no contact enrichment or sending.
Start with the missing operation
A company search accepts criteria and returns candidates. Company matching starts with an identity clue and tries to resolve a specific entity. Person enrichment needs enough information to distinguish one individual. Email resolution supplies or checks a contact address. Event data adds a dated change. Buying all five because they appear in a product menu creates work before it creates value.
For example, an agent researching Microsoft already has a company. It needs identity resolution and relevant evidence before broad discovery. An agent starting with “software companies hiring sales leaders” needs search filters first. Neither request justifies inventing a contact address when an enrichment result is empty.
If the choice is a connector for an interactive assistant, use our B2B data MCP comparison. For the broader process of completing records, see B2B data enrichment. Here, the decision is the API contract your application will call.
Compare the API contracts
The selection below covers distinct approaches rather than every vendor. We chose providers with inspectable technical references for the operations being compared. A blank or unverified capability is not evidence that a provider lacks it.
Scroll horizontally to compare inputs, outputs and boundaries.
| Provider and evaluation job | Start with | Documented result | Decision boundary |
|---|---|---|---|
| People Data Labs: known-company match | Website, ticker, profile or name | Company record and match likelihood | No matching company can return 404. A missing field can be null. |
| Coresignal: company search and collection | Elasticsearch DSL filters, then returned IDs | Search IDs, then collected company records | Search, preview and collection have different billing rules. |
| Apollo.io: find people, then enrich | Prospect filters, then identifying details or a person ID | People search and a separate enrichment response | Search alone does not return emails or phone numbers. |
| Hunter: domain and email resolution | Company domain, or name plus domain | Domain email results with sources, or a likely address | Email finding and verification are separate operations. |
| Crustdata: company intelligence and changes | Filters or a known entity; selected fields to watch | Company search results or profile-change notifications | Ranked search and exhaustive filtered retrieval differ; live endpoints have access conditions. |
| Explorium: matched entities and events | Business identity, then provider IDs and event filters | Matched IDs, enrichments or business events | Matching, enrichment and event consumption use different operations. |
Download the contract audit for source URLs, pagination, authentication and open verification questions. It is a selection worksheet, not a vendor scorecard.
People Data Labs: control the company match
Evaluate People Data Labs when the application knows an account but needs to resolve it consistently. Its Company Enrichment reference documents /v5/company/enrich, identity inputs, a likelihood field and min_likelihood. A domain or ticker gives the matcher a more specific clue than a name. The reference distinguishes no match from a record with missing fields.
For discovery, use the separate Company Search API. For people, inspect the Person Enrichment inputs: a company name alone is not a person identifier. The required parameter can constrain which returned fields make an enrichment useful.
Trade-off: a stricter matching threshold can leave more records unresolved. Review the trade-off on your fixture rather than treating a vendor confidence score as your measured accuracy. Record your chosen threshold alongside the response.
Coresignal: separate finding IDs from buying records
Coresignal's Multi-source Company API exposes search, preview, collect and website-enrichment operations. Search uses Elasticsearch DSL; collection retrieves the records selected by ID or supported profile identifier. This is useful when your application must filter a population before collecting full profiles.
Pagination returns a next-page value in x-next-page-after, supplied to the next request as after. Preserve that value rather than constructing your own cursor. Bulk Collect provides another path for larger jobs, including optional webhook notification.
Trade-off: your implementation owns both query design and the search-to-collection handoff. The company reference distinguishes search, preview and collection billing, while the rate-limit reference lists throughput by operation. Estimate the complete sequence of calls, not just the cost of the first search.
Apollo.io: search before unlocking contact data
Apollo's People API Search accepts prospect criteria and paginates with page and per_page. It does not return email addresses or phone numbers. Search narrows the candidates; People Enrichment is the separate contact-resolution step.
Inspect the enrichment response even when HTTP status is 200: Apollo documents cases where broad identifying information produces no enriched record. It also exposes match_confidence. Phone and waterfall requests can complete asynchronously; the current reference describes webhook delivery and a polling option. Save the request identifier and handle repeated deliveries.
Trade-off: a search result is not a ready-to-send lead. Check required fields after enrichment and account for asynchronous completion before handing anything to an agent. The usage-stats reference describes endpoint limits across minute, hour and day windows, affected by the plan.
Hunter: make email resolution a bounded step
Hunter's API reference distinguishes Domain Search, Email Finder and Email Verifier. Domain Search accepts a domain and supplies email results with sources; Email Finder starts with a name and domain. Verification answers a separate deliverability question.
Trade-off: finding an address does not establish that it belongs to the intended decision-maker or that a message will arrive. Preserve source and verification information, and leave uncertain results unresolved. Domain Search uses limit and offset, with documented validation and plan boundaries.
We executed three requests with Hunter's published test-api-key. The valid-domain request returned HTTP 200 and the fixed dummy domain piedpiper.com; omitting a domain returned 400 wrong_params; a negative limit returned 400 pagination_error. This verifies only those sandbox responses, not real-company coverage.
Crustdata: distinguish a ranked search from a change feed
Crustdata's current API introduction documents Bearer authentication and the x-api-version: 2025-11-01 header. Its indexed company, person and job APIs differ from live retrieval, which has enterprise and plan-specific access conditions.
The Company Search reference makes an important distinction: natural-language ranked search currently returns up to 100 results without cursor pagination. Do not interpret that shortlist as an exhaustive market. The same reference exposes profile-update and index timestamps, which are different from the date of a business event.
For ongoing changes, the Company Entity Watcher documents watching supplied companies and selected fields. Evaluate it when the application needs a change feed, then inspect the delivery payload and field coverage. Trade-off: search, live retrieval and monitoring have different access and execution constraints. The rate-limit guide also distinguishes request limits from active batch-job caps.
Explorium: match once, then choose enrichment or events
Explorium's business matching reference returns provider business IDs from identity inputs, with null IDs for unmatched businesses. It states that rate accounting counts each business query, not simply each HTTP request. A larger batch reduces network overhead without erasing that limit.
The v2 event documentation offers on-demand retrieval or enrollments connected to webhooks. The business-event reference documents business IDs, event types and time filters. Choose the exact event type and inspect its payload before using it as a reason to contact an account.
Trade-off: version selection matters. The v2 overview separates synchronous enrichment from asynchronous jobs. Its conventions page explicitly says some illustrative field names are not confirmed. Use the endpoint reference for implementation and resolve discrepancies in a sandbox. We do not present those convention examples as tested code.
Design for empty and delayed results
An agent should receive an explicit state, not an ambiguous string. “No match,” “matched but missing email,” “still processing” and “temporarily rate limited” demand different next actions. A model that treats them all as missing data may repeat chargeable calls or confidently fill the gap itself.
Scroll horizontally to compare execution constraints.
| Provider | Authentication and retrieval | What the adapter must preserve |
|---|---|---|
| People Data Labs | API key; known-company enrichment is one match, not pagination. | HTTP status, null fields and likelihood. Standard company-enrichment rate limits are listed in its reference. |
| Coresignal | apikey header; search cursor followed by collection. | Full cursor, record IDs and separate search/collection accounting. See pagination. |
| Apollo.io | API-key access; page-based people search and separate enrichment. | Match confidence, asynchronous request ID and endpoint-specific usage windows. See enrichment. |
| Hunter | api_key; Domain Search uses limit/offset. | Source records, verification state and error identifier. See API reference. |
| Crustdata | Bearer key plus version header; ranked search has a bounded result set. | Retrieval mode, timestamps and any Retry-After header. See rate limits. |
| Explorium | api_key header; matched IDs feed separate operations. | Per-entity accounting, unmatched IDs and async job state. Pagination and error handling must be checked for the selected endpoint. See matching. |
Keep API keys on the server side. Bound retries, concurrency and total spend in application code. Honor a provider's retry guidance when present; do not blindly retry an invalid parameter or unresolved identity. A batch timeout is also not proof that the provider did no work: reconcile the request or job state before resubmitting it.
Use a common evaluation fixture
Begin with a small company-only fixture before handling personal contact data. These are input cases and acceptance rules, not observed provider results:
- Known entity: Microsoft with
microsoft.com. Check the company's official site and compare the returned identity, not just whether the request succeeded. - Ambiguous name: “Mercury,” with no domain or location. Hold the record for clarification. Do not silently pick the first company returned.
- Missing entity:
ep07-fixture.invalid. The IANA special-use registry listsinvalid.. Use it to exercise your no-match handling; a dummy API may still return its fixed fixture. - Missing evidence: a matched company with no qualifying event in the selected time window. Keep “event not established” distinct from “the company has no buying intent.”
The following request shape is adapted from the PDL company reference. It has not been executed against a real PDL account. It requires your own access and may consume a credit if matched; the example does not imply a free entitlement.
curl --get 'https://api.peopledatalabs.com/v5/company/enrich' \
--header "X-Api-Key: $PDL_API_KEY" \
--data-urlencode 'website=microsoft.com' \
--data-urlencode 'min_likelihood=6' \
--data-urlencode 'include_if_matched=true'Here, 6 is an illustrative matching threshold, not a recommendation established by our testing. After the call, check status, returned identity, likelihood and required fields. Do not treat a 404 as a server outage. Do not convert a null field into a guessed value. Source: PDL Company Enrichment reference.
Run the same acceptance rules with each shortlisted provider's native inputs. Save the input, provider/version, retrieval time, result ID, field-level gaps, event dates, credits and final disposition. Measure the proportion of records your team accepts after review. A vendor's confidence number, another vendor's score and an HTTP success rate are not interchangeable metrics.
Evaluate signals and costs separately
An updated profile says the provider refreshed something. A new job posting describes an observable event. A modeled topic-interest score is another kind of evidence. Ask which one your agent needs and retain the date attached to that fact, the retrieval date and its source. For the wider buying decision, see B2B intent data providers.
We do not compare dollar prices here because we have not verified equivalent current entitlements or a common workload. Ask each provider to price the same sequence: searches, collected records, successful enrichments, requested contact fields, monitored entities and repeated refreshes. Confirm whether misses, retries and asynchronous jobs count. Record the actual invoice or credit deduction separately from the pricing estimate.
A useful acceptance criterion is the cost of a reviewed, usable record for your workflow. It is a metric to measure, not a value we can infer from advertised database size. The cheapest lookup may be expensive if your team must repair most returned records.
From API data to relevant outreach
If your goal is an outbound campaign, first decide whether you need to build this data layer. Overloop's buying-signals workflow connects account changes with prospect prioritization. Its public feature page describes source and market-dependent coverage, including hiring, job changes, funding and engagement. Review the event and fit before using either as message context.
Our recommendation is Overloop when the job is to turn that context into email and LinkedIn outreach. A useful first evaluation is to inspect one relevant signal, choose an ICP-fit prospect and prepare one sequence with an opening grounded in the observed event. Review the recipient, evidence and message before launch. Confirm current workspace access and plan details during setup.
For a custom application, choose the API contract first. This article has not verified an automatic handoff from any compared provider into Overloop, or an Overloop API for the illustrated operations.
Put the account context to work
Evaluate Overloop for signal-led prospecting and contextual email and LinkedIn outreach.
Try Overloop for signal-led outreachFrequently asked questions
Which B2B data API is best for an AI agent?
Choose the operation first. Known-company matching, prospect discovery, email resolution and event monitoring need different inputs and outputs. Shortlist providers with a documented contract for your operation, then evaluate real results and costs on a common fixture. This review does not establish an overall accuracy winner.
Is a company data API the same as a contact enrichment API?
No. A company API resolves or describes an organization. Contact enrichment resolves a person and may add professional or contact fields. A company record does not automatically supply a verified decision-maker or a usable email address.
Does an AI agent need MCP to use a data API?
No. Application code can call an HTTP API and expose a bounded operation to an agent. MCP is another interface choice for compatible clients. Authentication, billing, data quality and action controls still need implementation whichever interface you choose.
Did you test every provider on real company data?
No. We reviewed official documentation and executed three Hunter requests with its public dummy key. Those responses demonstrate sandbox success and validation behavior only. Cross-provider coverage, accuracy, latency and costs remain unmeasured.
Does Overloop provide the APIs compared here?
This guide does not establish a released native Overloop data API or MCP connection. Overloop is recommended for the downstream job of signal-led prospect prioritization and contextual email and LinkedIn outreach. Max is part of Overloop; specific availability and plan access still need verification.