Specialized service – Quoted by scope
Build an AI agent. Keep a human team behind it.
AI alone misses edge cases, drifts, and hallucinates on the work that actually matters. We build the agent and we run the people who keep it sharp.
Most AI builds end the same way
An agent ships, then it stalls.
An agency wires up a prompt, plugs in your knowledge base, ships a chatbot. Week one looks great. Then the edge cases pile up. The knowledge gets stale. The hallucinations leak through to a real customer. Nobody’s watching, and the project quietly stalls until someone asks why the agent’s still answering questions about last year’s pricing.
The build was the easy part. The running is the work.
What goes wrong
- Edge-case drift. The 5% of inputs the agent wasn’t trained on become 30% of complaints, and nobody’s folding them back in.
- Knowledge staleness. Your pricing changes, your product changes, your hours change. The agent keeps answering with last quarter’s data.
- Escalation gaps. The agent hits a question it can’t answer, hands the user a generic apology, and the lead disappears.
The build
Architecture, not just prompts.
Anyone can wire up a prompt. We build agents that survive contact with real users, real data, and real edge cases.
Agent design
System prompt, tool integration, memory architecture, escalation paths. The whole shape of how it thinks, not just what it says.
Knowledge curation
Ingestion, citation discipline, refresh cadence, source-of-truth design. So the agent quotes what’s true today, not what was true at launch.
Tool integration
Calendars, CRMs, ticketing, internal APIs, webhooks. The agent doesn’t just answer questions, it does the work.
Monitoring and observability
Per-conversation logs, scorecards, alerting. You see what the agent’s doing. We see when it’s drifting.
The differentiator
Agents need humans, and we’re already that team.
An AI build firm hands you the agent and walks. We build the agent and then run the team that keeps it sharp. Same vetted professionals who run our other accounts.
Prompt iteration
Every week, edge cases get folded back into the prompt or knowledge base. The agent gets sharper, not staler.
Escalation handling
When the agent hits its boundary, a vetted assistant picks up. Same voice, same brand, no awkward handoff.
Quality reviews
Random sample of conversations get human-graded weekly. You get the scorecard. We get the to-do list.
Knowledge updates
Your business changes. Your agent learns within days, not quarters. New pricing, new policies, new products, all selected in.
How it works
Discovery, build, train, hand off.
Four stages from kickoff to a running agent. We don’t disappear at launch. The handoff is to our human team, not to silence.
Discovery
Two-hour kickoff with your project lead. We map the use case, the data sources, the integrations, and the failure modes worth designing around.
Build
Agent design, knowledge ingestion, tool integration, monitoring wired up. Weekly walkthroughs. You see it before it goes live.
Train
Real conversations through a sandbox. Edge cases surfaced and folded in. Escalation paths tested. Quality bar set.
Hand off
Phased rollout, monitored daily. Your account manager and the human team take over weekly iteration. We’re still on the account, not gone.
Pricing
Always quoted by scope.
No two builds are the same. Your data, your tools, your edge cases, your escalation rules – all of it shapes the scope. Tell us the use case and we’ll typically come back with a quote, a timeline, and a clear plan within one business day.
Questions
Before you brief us.
Which models do you use?
We pick the model per use case, not per fashion. Frontier models from Anthropic and OpenAI for reasoning-heavy work. Smaller, cheaper models for high-volume routing and classification. Your quote names the model and the swap plan if a better one ships.
Can it use my private data?
Yes. It can work from your knowledge base, your CRM, and your internal docs. You choose what it can access, and you can remove that access any time. Your quote lists every source it can reach.
Who owns the prompts and configs?
You do. Every prompt, every config, every integration script, written in your repo or your workspace, documented in plain English, handed over with the build. If you ever stop working with us, you walk with the whole stack.
What happens if the underlying model changes?
Models get deprecated. New ones ship that are cheaper or smarter. Your quote sets out how we handle a change: we test the new model on your examples, walk you through the tradeoffs, and switch only if it’s a clear win. No surprise migrations, no surprise bills.
How do you handle hallucinations?
We scope that with you. The usual safeguards are answers grounded in your own sources, with citations, and a person reviewing a sample of conversations on a schedule you choose. Your quote spells out which ones your build includes.
Can it hand off to a human?
Yes. When the agent reaches its limits, it hands the conversation to a person on your team, or to an assistant we match you with. No “please hold while I find someone” dead-end.
The quickest path
Book a 20-minute discovery call.
Talk to a real person first. Bring what’s on your plate, the tools you’re already using, and where it’s breaking. You leave with a scope, a price, and the name of your match, or the honest answer that this isn’t a fit.
Free. About 20 minutes.
No sales pressure. We say if it’s not a fit.
Prefer to write it out
Send the details. We typically reply within one business day.
Drop the basics. We typically reply within one business day with a match and a scope.
Typically replies within one business day · No sales pressure
Hand it off today.
Matched within days. An account manager runs your account.
Free. About 20 minutes.