Answers grounded in your API
An AI agent that answers only from your workspace-scoped API context, cites every source, and hands off when the evidence isn't there.
You can see exactly why it answered
Every answer is assembled from your workspace context and carries the sources behind it. Open the citation, check the evidence. When the evidence isn't there, it clarifies or hands off instead of guessing.
Most support bots are confident and wrong.
Retrieval, not recall
Every answer is assembled from workspace-scoped API context and recent conversation — not the model's training memory.
Cited or it doesn't ship
Claims carry inline citations you can open. If the agent can't ground a statement, it says so and clarifies or hands off.
Injection-aware
Source content and user input are treated as untrusted. Redaction and careful mode keep prompt-injection attempts from leaking or misfiring.
A confident chatbot is worse than no chatbot
Generic AI support reads your docs and then improvises around the gaps — inventing endpoints, guessing auth rules, and stating made-up behavior as fact. For an API company, one hallucinated response can send a developer down a debugging path that never terminates. Trust erodes on the first wrong answer.
Answers built from evidence you can open
The agent retrieves the most relevant chunks of your API context, drafts an answer, and attaches the exact sources behind it. Reviewers and customers can click straight through to the endpoint, doc, or schema that backs each claim.
- Inline citations to endpoints, docs, and schemas
- Answers scoped strictly to your workspace context
- No claim without a source behind it
Low confidence clarifies — it never bluffs
The agent scores how well the evidence supports a question. Strong context yields a grounded answer; weak or missing context triggers a clarifying question or a clean handoff, with the reason recorded for the operator.
- Explicit confidence signal on every response
- Insufficient-context cases ask or escalate
- Careful mode raises the bar on sensitive threads
Safe with untrusted input and secrets
Ingested docs and customer messages are never trusted blindly. Credentials are redacted before they reach the model, prompt-injection patterns are contained, and operators get a sanitized debug trace that never exposes secrets or provider internals.
- Credentials redacted before every model call
- Prompt-injection resistant retrieval and prompting
- Operator-only debug traces, secrets stripped
How a question becomes an answer.
Retrieve the evidence
The agent pulls the most relevant workspace-scoped context for the question at hand.
Draft with citations
It composes an answer grounded in that evidence and attaches the sources it used.
Grade and route
High confidence sends a cited reply; low confidence clarifies or hands off with a reason.
Grounded AI agent questions
How does the agent avoid making things up?
It only answers from workspace-scoped API context and recent conversation, and it attaches citations to its claims. When the evidence isn't there, it clarifies or hands off rather than inventing endpoints, fields, or behavior.
Which AI provider or model does it use?
Provider and model routing is a platform concern handled on the backend. It isn't exposed as a customer-facing setting, so you get grounded answers without managing model plumbing.
Is it resistant to prompt injection?
Ingested content and user input are treated as untrusted. Credentials are redacted before model calls, injection patterns are contained, and the operator debug trace never exposes secrets or provider internals.
Can operators see why it answered the way it did?
Yes. Every reply carries a sanitized, operator-only trace showing the retrieved context and reasoning, with sensitive data stripped out.
Put a grounded agent on the front line
Let an agent that cites its sources — and refuses to guess — handle the first reply on every channel.