Your agents, your data,
full speed.

Built for agents from the ground up, not a chatbot glued on afterwards. Anything you can do in AnalystX, your agent can do too.

Query the pipeline, write up a company, move a round, draft the LP update. Let your agents tap into an advanced MCP, or connect the rest of your custom tech stack via OpenAPI.

ClaudeChatGPTGeminiGrok
You typed this once

“Go through the twelve companies from demo day. Which have we seen before, who do we know at each, and which fit our thesis?”

  1. The list

    It looked up all twelve companies.

    What they do, where they are and what stage they're at, part from enrichment and part from the agent going and reading. The ten minutes of searching you would have done before every intro call.

  2. Already seen

    Three of them are not new to the firm.

    One we saw at pre-seed in 2024 and passed. One asked us for a term sheet comparison last spring. One is already in the pipeline under a slightly different name.

  3. Who we know

    It found the warm routes in.

    A partner met one of the founders at a conference in 2023, and someone on the team has been in a thread with another since the spring. Read out of the firm's own mail and calendars, not guessed at.

  4. Written on the record

    Everything it found is written on the company.

    A short paragraph in ordinary sentences, so you can read it before the call instead of opening six tabs on your phone.

  5. Worth your time

    It put them in order against our thesis.

    The four that look like real work are at the top and the ones outside your stage or geography are at the bottom, and it explains in a sentence why it thinks so.

  6. The first line

    It drafted the opening of each reply.

    Each one mentions what that company actually does, so the founder can tell you wrote to them and not to twelve people at once.

  7. Where it stopped

    Two of them it left alone on purpose.

    One is in a competitor's portfolio already, and one is outside the fund's mandate. It told you both, rather than putting them on your call list.

  8. Your morning

    Then it told you who to call first.

    Three names in order, each with one line on why. All of this was finished before you sat down with your coffee.

Connect it
in a minute.

AnalystX was built agent-first: a full MCP surface over every record, so the assistant you already pay for works inside your fund rather than talking about it.

  • Works with the assistant you already have, Claude, ChatGPT, Gemini or Grok, added as a custom connector in their settings. No new subscription, no vendor to standardise on, no seat for an AI you didn't ask for.
  • It reads the manual first, because the server ships skills, not just tools. Before it touches anything, it loads written guidance on how records, mail, notes and views actually work here. Most MCP servers hand a model a pile of tools and hope.
  • It signs in as you, over OAuth, so it sees exactly what you can see and nothing else. If a junior can't open the LP records, neither can their agent.
  • You stay in charge, because the agent asks before it acts. It shows you what it intends to do and you say go. Point it at the pipeline and leave the sending to you.
  • OpenAPI for the rest of your stack, so whatever your fund has built already can read and write the same records the agent does.

Questions about
agents.

What can an agent actually do inside our workspace?
Anything you can do. Query the pipeline, add a company, move a round, merge duplicates, read and search the firm's mail, write up a call, draft a reply from a template, run a published workflow, even change the shape of your tables. It acts in AnalystX rather than describing it from the outside.
Do we have to change assistant?
No, and that is the point. Claude, ChatGPT, Gemini or Grok, whichever your firm already pays for, added once as a connector. No second AI subscription and no vendor to standardise the partnership on.
Can it see things it shouldn't?
It signs in as you over OAuth, so it sees exactly what you see and nothing more. If an associate cannot open the LP records, neither can their agent. There is no API key to paste or leave lying around.
How do we know what it did?
Everything it does is written onto the company in ordinary sentences, so you read it back rather than trusting it blindly. It also tells you where it stopped on purpose and left something alone.
Is this just a chatbot in the corner?
A chatbot can talk about your data. An agent can act on it: go through twelve companies from demo day, work out which ones the firm has already seen, write what it found onto each record, rank them against your thesis and draft the opening line of each reply, before you sit down with your coffee.
What about the rest of our stack?
If your team has built something internal, it can talk to AnalystX too. We publish an OpenAPI spec covering the same records the agent works on, so your own code reads and writes the same data. Use MCP when an agent is doing the work, and the API when your code is.

Your agent, your data,
today.

Request access and we'll have you running under a week.

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