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Service and operations
Support that answers from your own record and hands off with the context.
An AI customer service agent answers from your documentation and account data, cites the source for every answer, takes the routine actions your systems allow, and escalates anything irreversible to a person with the whole thread attached.
Who it is for
Built for the team that does this by hand.
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.
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.
Takes bounded actions
Status lookups, address changes, plan switches within limits, appointment moves: the actions your systems expose and you approve in writing.
Escalates with the thread
Refunds, cancellations, complaints and anything it is unsure of go to a person with the conversation, the account and a suggested reply already attached.
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.
Every system here is scoped as one bounded workflow with a written success metric and a kill threshold agreed before the build. The steps below are the ones specific to this one.
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, not a guess.
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, supervised
The agent answers and acts within limits. Refunds, cancellations and anything irreversible wait for a person. The handoff rate tells you where to widen it next.
Where this stands
What we run today.
The harness is the one our own always-on operator 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.
Governance
What a person still approves.
- 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.
Price
Published, not gated.
Pilot builds $25,000 to $60,000 fixed, production retainer from $8,000 per month. Every AI build starts with a $7,500 AI Opportunity Audit over two weeks that is credited toward the build if you proceed, and a pilot is one bounded workflow on your real data over 30 to 90 days with a written success metric and a kill threshold.
The full price list is on the pricing page, and the cost drivers, with the questions that expose a padded quote, are in how much AI agents cost in 2026.
Questions
Customer support agents, answered.
What is an AI customer service agent?
How much does an AI customer service agent cost?
Can it work inside Zendesk, Intercom or HubSpot Service Hub?
Related
Where this connects.
AI workflow automation · Internal knowledge assistants · HubSpot and CRM implementation
The other systems in the catalogue: lead qualification agents, outbound sales agents, document processing agents, internal knowledge assistants, ad optimization systems, client reporting automation, content engines, computer vision systems, mcp servers and agent-callable surfaces, always-on operations agents.
Teams we've helped grow
Pilot builds $25,000 to $60,000 fixed, production retainer from $8,000 per month
Real ranges, published. Ad spend stays in your own accounts.
See the full pricing table →Where this fits: see the Strataigize Growth System, the ladder every engagement runs on.
Talk to the build team about customer support agents
Name the workflow you want it to run and we reply within 24 hours with whether it is a fit, the bounded scope we would propose, and the payback math.
Start with one workflow.
A free 30-minute audit call with the senior team names the workflow this system should run first and what it should cost, whether you build it with us or not.
Book your growth audit →Canadian and looking at funding? How the BDC LIFT program works. Public sector? How we build for government.
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