AI agents

The context layer for your AI agents

Claude, ChatGPT and your own agents reason better with Ocean behind them: company data, your fit scores and the buying committee, one call away.

Ask your AI how Ocean works as its context layer

Try the agent Get a demo

Ocean sits between your AI and your go-to-market data.

Claude, ChatGPT, Perplexity, Gemini and your own agent connect to Ocean over MCP and the REST API. Ocean gives them the company index, people profiles, segments and fit scores, signals and your CRM data.

Ocean · Agent
Find VPs of sales at Series B SaaS in Germany, 50–200 employees.

Try a prompt

The context layer

What your agent gets back

A model on its own has no view of your market. Ocean gives it the company data, your fit scoring and the buying committee to reason with.

  • Facts, not guesses

    Firmographics, technographics and people, structured so the agent cites them instead of inventing them.

  • Context that is yours

    Fit scores and segments come from your own won deals, so “good fit” means your definition.

  • One call, one answer

    The agent asks once and gets the profile, the score and the people back together.

Integrations

Ask in Claude or ChatGPT. Get your own data back.

Connect Ocean once. Any MCP client can search companies and people, score them and export the list to your CRM.

Everything an agent can use

One company index behind every tool. Your agent calls the same search, scoring and enrichment you use in Ocean.

  • Contextual intelligence

    Understand what each company really does.

    • Reads what companies actually do, not industry codes.
    • Describes what it sells and who it sells to.
    • Powers lookalikes and segments.

  • Segmentation

    Find the segments hiding in your closed deals.

    • Finds the segments in your won deals.
    • Win rate, deal size and cycle time per segment.
    • Tier 1–4 account recommendations.

  • Lookalike companies

    Find more companies like your best customers.

    • Start from your best customers.
    • Ranked matches with reasons.
    • Net-new and already-in-CRM accounts.

  • Search

    Filter the market down to the accounts you want.

    • Hard filters for an exact market count.
    • Company and people search.
    • Exclude what you don't want.

  • Enrichment

    Add the contacts behind every account you target.

    • Work email and phone.
    • Buying committee roles.
    • Contact data on demand.

  • API & MCP

    Bring Ocean into the tools you already use.

    • Use Ocean inside Claude and your own tools.
    • REST API.
    • Works where reps already work.

  • Data layer for AI

    Give every AI tool the company data your team uses.

    • One company index behind every agent and assistant.
    • Context vectors and fit scores for each company.
    • Reach it through the MCP server or the REST API.

  • Ocean Agent

    Ask for the accounts you want in plain English.

    • Searches, scores and exports in one run.
    • Works inside Ocean and any MCP client.
    • Uses the same data as the rest of Ocean.

  • Lead scoring

    Rank inbound leads against the segments that win.

    • Scores each lead against your segments.
    • Shows the fit score and the reason behind it.
    • Writes segment scores back to your CRM.

  • Workflows

    Turn every good list into a repeatable process.

    • Chain search, enrichment and CRM export.
    • Assign CRM owners by rules you set.
    • Notify each rep in Slack.

  • Signals and events

    Reach out when something changes at an account.

    • Filter companies by open job postings.
    • See buying signals in search and quick view.
    • Use signals in the API, MCP and Workflows.

  • Buying committees

    See who is in the room on every winning deal.

    • Built from the deals in your CRM.
    • Ranked in people search.
    • Edit a committee and see its people in recommendations.

  • Account briefs

    Walk into every call with context on the account.

    • Ask your MCP client for a brief on any account.
    • Pulls from the same company data as Ocean.
    • Saves the research before a first call.

  • Technographics

    Find companies by the software tools they run.

    • Filter by CRM, cloud and marketing tools.
    • Cover analytics, ad and support software.
    • Combine tech filters with firmographics.

  • Chrome extension

    Bring Ocean data to any company site you visit.

    • See company details while you browse.
    • Find lookalikes without leaving the page.
    • Add accounts to your lists as you go.
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Workflows

Write the play once. It runs on every deal.

Describe what should happen when a deal moves, and Ocean.io builds the steps: wait, research what changed, judge the fit, then sequence the right people.

What it can do

One agent, the whole go-to-market loop

Pick a job. These are real prompts and the tools the agent calls to answer them.

Describe the accounts. Get the list.

Company and people search in one conversation. The agent counts the market first, then pulls the list, so you see the size before you spend credits.

  • search_companies
  • search_people
  • count_companies
  • count_people

Try asking

  • VPs of sales at Series B SaaS in Germany, 50–200 employees
  • How many fintechs in the UK use HubSpot?
  • Companies hiring 5+ sales roles right now

Use cases

Teams use Ocean to size a market, find the segments that win and build lists that sales trusts. Choose the role closest to yours.

Plan territories on real market data

Size every segment and split accounts fairly across reps. Keep territories current as your market changes.

  • Exact market counts per territory.
  • Balanced account lists for every rep.
  • CRM sync that stays current.

Win rate by segment

  • Mid-market SaaS 68% win rate
  • Enterprise fintech 54% win rate
  • SMB e-commerce 41% win rate

What the best Mid-market SaaS accounts share

  • 3.4x Uses Salesforce or HubSpot
  • 2.7x Raised a Series B or later
  • 5.3x less Runs on-prem or self-hosted
Example view with sample data.

Know which segments win

See win rate, deal size and cycle time for every segment. Point your team at the accounts most likely to close.

  • Segment performance from your own deals.
  • Tier 1–4 account recommendations.
  • Clear priorities for every rep.

Win rate by segment

  • Mid-market SaaS 68% win rate
  • Enterprise fintech 54% win rate
  • SMB e-commerce 41% win rate
68%
Win rate
$28K
Average deal
270
Potential wins
Example view with sample data.

Build comprehensive account lists from one source

Run search, lookalikes and enrichment from the API or the MCP server. Send the results to the tools you already run.

  • REST API and MCP server.
  • Search, lookalikes and enrichment.
  • CRM integrations.

GET /v1/companies/lookalikes?domain=stripe.com

{
  "query": "stripe.com",
  "results": [
    { "domain": "adyen.com", "name": "Adyen", "score": 0.94 },
    { "domain": "checkout.com", "name": "Checkout.com", "score": 0.91 }
  ]
}
Example view with sample data.

Target accounts that look like your best customers

Start from your best customers and get ranked lookalikes with reasons. Build ABM lists that sales agrees with.

  • Ranked lookalikes with reasons.
  • Net-new and already-in-CRM accounts.
  • Buying committee roles for each account.

Roles in 38 won deals, by department

  • Sales 49
  • RevOps 29
  • IT & Security 24
  • Finance 13
  • Executive 13
Example view with sample data.

Start every day with a list worth calling

Get ranked lookalikes of the accounts you already win, with the contacts behind them. Spend your time on outreach, not on research.

  • Ranked matches with a fit score.
  • Work email and phone for each contact.
  • Send contacts straight to your sequencer.

Find lookalikes of your mid-market SaaS wins

  • Fit score94
    Brightwave brightwave.io
    4 contacts
  • Fit score91
    Northwind Systems northwindsys.com
    3 contacts
  • Fit score88
    Lumen Labs lumenlabs.io
    5 contacts
Example view with sample data.

Find your next hundred customers from your first ten

See what your first wins have in common and search for more companies like them. Learn which market to chase before you hire a team to chase it.

  • Patterns from your earliest deals.
  • Exact counts for each market you test.
  • Start free, with no commitment.

What your first wins share

  • 5.3x Runs on Shopify or BigCommerce
  • 2.8x Under 50 employees
  • 3.8x less Enterprise procurement process
Example view with sample data.

Size and build a client market in one session

Define a client market with hard filters and see how big it is before you commit. Hand over account lists with contacts and reasons attached.

  • Exact market counts for each client.
  • Lists with contacts and fit reasons.
  • Export to the client CRM or by webhook.
1,240 companies match
  • Industry
  • Technologies
  • Location
  • Employees
Example view with sample data.

Control

You stay in charge of the run

  • Every tool call is visible

    See which tool ran, with which filters and how many results came back.

  • Credits are reported

    Tools that spend credits return what they used and what is left, so a run’s cost is auditable.

  • You approve the writes

    Exclusions, segmentation changes and exports happen after you agree to them.

  • Same data as the product

    The agent reads the same company, people and CRM data you see in Ocean. No separate copy.

Connect

Up and running in three steps

  1. Add Ocean as an MCP server

    In Claude, ChatGPT, Cursor or any MCP client, add the Ocean server with the HTTP transport.

  2. Sign in

    Approve access with your Ocean account. Clients without sign-in can use an API token from Settings.

  3. Ask

    Try “Find VPs of sales at SaaS companies in Germany.” The agent picks the tools.

Claude Code 
$ claude mcp add --transport http ocean <MCP_BASE_URL>/mcp/ --header "x-api-token: <YOUR_API_TOKEN>"

> Find VPs of sales at SaaS companies in Germany

✓ search_people · 212 people

Questions

What is the difference between the Ocean agent and the MCP server?

The Ocean agent is the chat inside the web app, with tables and one-click exports. The MCP server gives the same search, scoring and export tools to the AI client you already use.

Which AI clients work with Ocean?

Any client that supports MCP over streamable HTTP, including Claude, ChatGPT and Cursor. Claude Code connects with one command.

Does the agent spend credits?

Searching and counting the market are the cheap steps. Tools that spend credits report what they used, so you can check a run’s cost.

Can the agent write to my CRM?

Yes, to HubSpot, Salesforce and Pipedrive, after you ask for an export. It can also read your deals to build segments.

Can I build on this without the chat?

Yes. The REST API exposes the same data, and Workflows chain search, enrichment and export on a schedule.

Put an agent on your pipeline

  • Describe accounts in plain English and get them in your CRM
  • Works in Ocean, Claude, ChatGPT and Cursor
  • Same data as the Ocean product and API
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