canonical: https://jentic.com/apis/databook.com/databook

# Databook AI

The Databook AI API retrieves account intelligence for B2B sales teams, searching companies by name and listing the professionals associated with each one. It generates sales assets from the asset studio, runs deep reasoning over a target account, and answers account questions through a chat endpoint. Batch jobs enrich lists of accounts asynchronously, returning results you can poll for once the job completes.

## For AI agents

Search companies, list their professionals, and generate sales assets through Databook AI. Run account reasoning, start account chats, and submit batch jobs to enrich lists of target accounts.

## Scope

Does not handle CRM record storage, email sequencing, or deal-stage tracking. Use for account intelligence and sales asset generation only.

## Capabilities

- Search for companies by name and pull the professionals associated with each account
- Generate sales assets from the asset studio library for a target account
- Run deep reasoning over an account to surface strategy and talking points
- Submit batch jobs to enrich a list of accounts and retrieve the results when ready
- Start a chat session to ask questions about an account in natural language
- List the account insights available for a target company

## Use cases

### Account Research Agent

An AI agent researches a target account end to end: it searches Databook for the company, lists the professionals attached to it, pulls the available insights, and runs deep reasoning to assemble strategy notes. The agent discovers each Databook operation through Jentic by intent, so it calls company search, the professionals lookup, and reasoning in sequence without hardcoding endpoint paths.

Example prompt: Search Databook for a company by name, list its professionals, then run deep reasoning on the account and return the strategy summary

### Pre-Meeting Sales Prep

A seller preparing for a meeting needs a briefing on the account. The agent searches the company, generates a sales asset from the asset studio, and lists the insights on file, producing a ready-to-read brief. Databook handles the asset generation server-side, so the agent only submits the request and reads the generated asset back.

Example prompt: Search for the target company, generate a sales asset for it, and return the generated asset along with the available account insights

### Bulk Account Enrichment

A revenue team wants intelligence on a long list of accounts rather than one at a time. The agent downloads the batch input CSV template, submits a batch job, polls for completion, and retrieves the per-account results. Databook processes the list asynchronously, so the agent fires the job once and collects results when the job finishes.

Example prompt: Submit a batch job for a CSV list of accounts, poll the job by its id until it completes, and retrieve the results

## Key endpoints

| Method | Path | Description |
| --- | --- | --- |
| GET | `/v1/asset/companies` | Search companies by name |
| GET | `/v1/asset/companies/{company_id}/professionals` | List professionals at a company |
| POST | `/v1/reasoning` | Run deep reasoning over an account |
| POST | `/v1/chat` | Create a chat session about an account |
| GET | `/v1/insights` | List available account insights |
| POST | `/v1/batch/job` | Create a batch enrichment job |
| GET | `/v1/batch/job/{job_id}` | Get a batch job by id |
| GET | `/v1/batch/job/{job_id}/result` | Retrieve batch job results |

## Key resources

- **Batch jobs** — Create batch jobs, download the input CSV template, and retrieve job results by id
- **Asset studio** — Browse the asset library, generate assets, and search companies and their professionals
- **Insights** — List the account insights available for a target company
- **Reasoning and chat** — Run deep reasoning and start chat sessions over a target account

## AI readiness

This API is usable in Jentic One now. Its AI-readiness score against Jentic's framework shows where it stands today and where improvements would make it even easier for agents to use.

- **Score:** 59 / 100
- **Maturity:** Foundational
- **Dimensions:**
  - Foundational Compliance: 93 / 100
  - Developer Experience & Jentic Compatibility: 69 / 100
  - AI-Readiness & Agent Experience: 44 / 100
  - Agent Usability: 94 / 100
  - Security: 60 / 100
  - AI Discoverability: 32 / 100
- **View full report:** https://jentic.com/apis/databook.com/databook/scorecard
- **How the score is calculated:** https://docs.jentic.com/reference/api-readiness-framework/overview/
- **More about the dimensions:** https://docs.jentic.com/reference/api-readiness-framework/specification/#dimensional-model-overview

### Score it yourself

Every API in the directory is allowlisted, so you can re-score it with no key required.

- **Score your own API:** https://jentic.com/scorecard.md
- **Scoring CLI agent skill:** https://github.com/jentic/jentic-api-scorecard/blob/main/skills/jentic-api-scorecard/SKILL.md

```sh
npx @jentic/api-scorecard-cli score <openapi-url>
```

## Why Jentic

- **Setup:** Wiring Databook by hand means managing its bearer token and sending the right user and tenant identity headers on every call. Through Jentic you install once, import Databook from the API Directory, store the token once, and your agent calls it.
- **Permission scoping:** You choose which Databook operations your agent may call, so you can allow company search and insight reads while leaving asset generation and batch job creation out unless you add them. Databook carries account and job identifiers in the request body and URL path, so rules bound which operations run.
- **Credential handling:** Your Databook token is stored once, encrypted, by your own Jentic One instance and injected at execution time. It never enters the agent's prompt, logs, or context.
- **Discovery method:** Agents search Jentic by intent such as find professionals at a company or run account reasoning, and Jentic returns the matching Databook operation with its input schema so the agent calls the right endpoint without reading the reference docs.

## Related APIs

- **Apollo.io** — Apollo covers contact and company prospecting data; Databook focuses on account intelligence and sales asset generation.
- **Clearbit** — Clearbit enriches a company or person record with firmographic attributes; Databook adds account reasoning and insights on top of company data.
- **Salesloft** — Salesloft runs the sales engagement cadences; Databook supplies the account intelligence that shapes the outreach.

## FAQ

### What authentication does the Databook AI API use?

The Databook API authenticates with a bearer token in the Authorization header, per its OpenAPI spec, and requests also carry identity headers that resolve the calling user and tenant. Through Jentic the token is stored encrypted by your own Jentic One instance and injected at call time, so it never lands in the agent's prompt or logs.

### Can I generate sales assets with the Databook AI API?

Yes. The asset studio operations let your agent browse the asset library, generate an asset for a target company, and read the generated asset back by its generation id. Pair it with the company search operation to resolve the account first.

### What are the rate limits for the Databook AI API?

The OpenAPI spec does not publish rate limits for the Databook API. Check Databook's own API documentation for the current limits that apply to your account, since access is provisioned per tenant.

### Can I limit what my agent is allowed to do with the Databook AI API?

Yes. Write a rule that allows only the read operations such as company search, the professionals lookup, and insight listing, so the agent can research accounts but cannot generate assets or create batch jobs unless you add those operations. Every call it makes is logged.

### How do I run account reasoning with the Databook AI API through Jentic?

Search Jentic for an intent like research a target account, store your Databook token once, and your agent calls the reasoning operation with the account it resolved from company search. To run it on your own infrastructure, install Jentic One from its GitHub repo.

### Is there a Databook AI MCP server?

You don't need an MCP server to give your agent the Databook API. Jentic connects it directly from the API Directory: import it, store your token once, and your agent calls the operations it needs on demand.