Chatbots that knowyour product.

Assistants that answer from your own data, run on your servers, and can't run up your bill.

  1. First callWeek 1

  2. Milestone pricedWeeks 1-2

    Answers from your own documents

    Generic chatbots guess. Yours should answer from what your business actually knows.

    The assistant answers from your own documents and data, and we decide what it may and may not touch before it's built.

    • Answers grounded in your content
    • Clear limits on what it can read and do
    • Logs you can review
  3. Working buildsWeeks 2-7

    A chatbot inside your app

    You want an assistant in your web or mobile app, not a widget bolted onto an FAQ page.

    We add AI chatbots to web apps and to Flutter, React Native or native mobile apps, connected to your product so they answer about the customer's own account, not just your help pages.

    • Web, iOS and Android
    • Answers about the user's own account
    • Hands off to a person when it should

    Your API key never ships in the app

    Someone suggested putting the OpenAI key in the app. Please don't.

    Every call goes through a server-side proxy that checks who is asking and how much they've used, so the key stays on your server and one user can't spend your budget.

    • Server-side proxy for every model call
    • Signed-in users only
    • Per-user quotas and spending limits
    Crumb Count. AI calls through a server-side proxy with per-user quotas.
  4. Broken on purposeBefore launch

    Prompt injection and abuse testing

    A chatbot is a new way in. Someone will try it.

    We try to break it before your customers or attackers do: prompt injection, untrusted content in tool results, forged sessions and attempts to burn your budget.

    • Prompt injection attempts
    • Untrusted input through tools and files
    • Cost and abuse attacks
    Crumb Count. Adversarial tests for JWT forgery, key confusion and cost attacks.
  5. Handed to youWeek 8

Questions, answered.

Can the chatbot see our customers' data?

Only what we decide together it should, enforced on the server, not by asking the model nicely.

Which model powers it?

Usually OpenAI's models to start, compared against alternatives for your case before we commit.

How do you keep the cost under control?

Spending limits per user and a server that chooses the model, so a single user or attacker can't run up the bill.

Does it work in our mobile app?

Yes, in Flutter, React Native or native apps, with the AI calls going through your server.

Start with a free call.

15 or 30 minutes with the engineers who would write your code. If we're not the right fit, you hear it on that call.