Support that answers from your own record and hands off with the context.

Answer repeat questions from your help documents and account records, with the source attached. You define the actions the system may take; unsupported answers and cases outside those limits go to your support team.

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Who it is for

Teams that need this workflow.

SaaS and subscription businesses where most tickets are the same dozen questions

Service businesses fielding booking, billing and status requests after hours

Public services answering the same eligibility and status questions at volume

What it does

Customer support agents, by the job.

Answer

Answers with citations

Every answer points to the article, policy or account record it came from, so a customer or an auditor can check it instead of trusting it.

Act

Takes bounded actions

Status lookups, address changes, plan switches within limits, appointment moves: the actions your systems expose and you approve in writing.

Escalate

Escalates with the thread

Refunds or cancellations beyond your limits, complaints and anything it cannot verify go to a person with the conversation, the account and a suggested reply attached.

Measure

Measures what changed

Resolution rate, handoff rate, time to first answer and customer rating, reported beside the pre-agent baseline rather than in place of it.

How it is built

The build, in order.

The pilot covers one defined workflow. We agree its success metric and kill threshold in writing before the build; the steps below show how this system is developed and evaluated.

Read the ticket history

The top intents by volume and by cost, which ones have a written answer, and which ones a person must always handle. The scope is the list that survives that read.

Build the knowledge base

What the agent may answer from, what it may not, and what happens when the corpus is silent. A question with no source gets a handoff.

Shadow on live tickets

The agent drafts, your team sends. Every edit your team makes to a draft is read, and the disagreements tune it before it speaks to a customer.

Go live on its own

The agent answers and acts within your limits, refunds and cancellations included, and checks every action against them. What falls outside goes to a person, and each resolved handoff is added to what it can answer next time.

Where this stands

What we run today.

The harness is the one our own AI Operations Agent runs on: it answers the team in Slack, runs scheduled jobs, and is held to a standard of knowing its own activity without a gap. Our public MCP server lets an AI assistant query our business the way a support agent would query yours. We have not published a customer-facing support deployment yet, so the first one is priced as a pilot like every other build on this page.

Chuck, our AI Operations Agent

Governance

Controls and human review.

Refunds, cancellations and account changes beyond written limits always route to a person
Every answer carries its source, and an answer with no source is not sent
Conversation logs are retained under your policy and never used to train a shared model

The rest of the posture is published on trust and security: client-granted access you can revoke, credentials in managed stores, an AI governance summary aligned to the NIST AI Risk Management Framework, our subprocessors, and a DPA on request. We do not hold SOC 2 and we say so there.

Questions

Customer support agents, answered.

What is an AI customer service agent?

Software that reads a customer's message, answers from your documentation and account data with the source cited, and takes the actions your limits allow. What falls outside them goes to a person with the thread attached. The scope includes the approved actions and the handoff to your support team.

Can it work inside Zendesk, Intercom or HubSpot Service Hub?

Yes. The agent reads and writes through the help desk's API, so tickets, macros and reporting stay where your team already works. We build to the platform you have.