Demos are easy. Agents that keep receipts.
AI agent development for real business operations. Every agent is grounded in your data, held inside bounded tools and human gates, and tested against known cases before it goes live, then watched after. It plugs into the stack you already run.
100% in-house development · Oregon & California, USA · 25+ years building production systems
The agent contract, illustratedConsumer guide: AI attendants
The short answer
Updated September 2026
Houtos Labs builds AI agents for production work and designs them to leave a trace of every step. Internal ops agents, customer-facing assistants and multi-agent workflows. Each one is built to answer from your data with citations, work inside bounded tools and human approval gates, and pass an evaluation suite before and after deployment. They live in the tools you already run, so nobody has to remember to open another app.
The rule we hold agents to is the one this studio runs on: an estimate is never dressed up as a measurement, and any agent action that matters gets a human gate. (Plain-language primer: should your business have an AI attendant?) Store-side automation lives in our e-commerce practice.
A sales agent that quotes from the price book and escalates the rest
A live-chat sales agent for an imaginary appliance repair company. It answers from the service catalog, tells the truth about prices, and stops at a gate where money moves. Pick a reply and watch it work the lead.
The first reply often decides the lead
If nobody picks up, the customer calls the next shop on the list. The agent answers in seconds, quotes only from the real price book, and books real calendar slots. Anything unusual goes through a human gate.
- Grounded. Answers cite the service catalog and route map
- Gated. Discounts and exceptions escalate to a human
- Logged. The full transcript lands on the tech's job board
Scripted demonstration with a fictional company. A real deployment answers from your catalog, prices and calendar.
My washer is leaking from the bottom mid-cycle.
2:14 PMSorry about that. A mid-cycle leak from the bottom is usually a door seal or the drain pump, and both are same-visit fixes. I can have a tech at your place tomorrow between 9–11 AM. Want me to hold that slot?
Summit Assistant · 2:14 PM · sourced from the service catalogHow much will it cost?
2:15 PMFair question. The visit + diagnosis is $89, credited toward the repair. A door seal runs $140–$190 installed; a drain pump $180–$240. The exact number is confirmed on-site before any work starts, so there are no surprises.
Summit Assistant · 2:15 PM · price book v2026-06Book it
2:15 PMDone: tomorrow, 9–11 AM is held for you. You'll get a text confirmation and a 30-minute heads-up when the tech is on the way. 👍
Summit Assistant · 2:16 PM · calendar + job board updatedScripted demonstration · fictional company · no data leaves this page. A real deployment answers from your catalog, prices and calendar.
The revenue loop, end to end
One agent system that carries a customer from first contact to repeat business. This is the workflow we design and build, with a human placed exactly where judgment matters.
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01
Lead intake
Forms, chat, phone and social messages land in one queue. Nothing sits in a voicemail box.
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02
Profile build
The agent builds a picture of the customer: location, property type, urgency, likely budget range.
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03
Tailored first response
Written in the customer's own tone, from the real catalog. Design target: under 5 minutes.
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04
Sales handoff
Your rep gets the profile and a suggested approach: pace, proof points, and what this kind of customer responds to.
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05
Funnel management
The agent project-manages the deal for the rep: reminders, next steps, stalled-deal flags.
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06
Close
A human closes. The agent preps the documents, the scheduling and the welcome sequence.
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07
Review capture
The same review request goes to every customer after the job. Asking only the happy ones is review gating, which Google prohibits.
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08
Care loop ↺
Scheduled check-ins, service reminders and upsells that fit what they bought. Recurring revenue and referrals, then back to 01.
Amber nodes are human gates. "Under 5 minutes" is the design target we build against. It isn't a universal guarantee: your volumes set the final SLA in the scope.
An agent run, traced
This is what "production-grade" looks like: a disciplined loop that keeps receipts. Pick a task and watch the trace.
Same loop every run:
ground → plan → act →
verify → hand off
- groundread ledger · 4 invoices >30 days overdue, histories attached
- plantone per customer history: 3 gentle · 1 firm
- act4 reminder drafts written, amounts reconciled to the ledger
- verifyamounts re-checked against source · 4/4 match
- gatehuman approves before anything sends. The agent never sends a message about money on its own
- donequeued for approval · full trace logged
Scripted demonstration. The loop, the gates and the logging it shows are the real architecture we ship.
Evaluation discipline: how we grade.
What our agent development covers
From one well-guarded assistant to a coordinated team of agents, scoped in writing and gated where the risk lives.
Internal ops agents
Invoice chasing, record reconciliation, report compilation, inbox triage. The repetitive work that eats your team's week, done with receipts, and with a human gate on anything consequential.
Customer-facing assistants
They answer from your real docs and policies, admit what they don't know, and hand off to a person without fumbling. An attendant that helps your customers, instead of a chatbot that embarrasses you.
Multi-agent systems & orchestration
Specialist agents coordinated through shared state, verification lanes and clear ownership. We run these patterns in our own operations and apply them to yours.
Evaluation & guardrails
This is the part that makes it production-grade: eval suites against known cases, bounded tool permissions, action logging, and monitoring after deploy. If it can't be graded, it doesn't ship. That's the studio rule, applied to agents.
If you can't replay the run, you can't trust the agent.
Cited answers · bounded tools · human gates where the risk lives
We build agents the way we use them
The standing rule: the trace above says "scripted" on its face because it is. The architecture it shows is real, and this studio runs on the same discipline every working day: multi-agent workflows, verification lanes and written standards.
Agent systems, by status
The Intelligence Desk and Companion Systems are concepts, and the Registry labels them that way.
The MethodThe rubric, published
The written standard our agents are evaluated against.
The Owner's ManualThe plain-language primer
What an AI attendant can and can't do, in a guide written for owners.
The Design StudioThe interface side of the craft
Seven working exhibits on one page, from typography to keyboard access.
Fair questions
What is business AI agent development?
It means building AI systems that do real work inside real operations. They read the tools you already run (email, CRM, tickets, spreadsheets, databases), reason through a task and take bounded actions. Then they get evaluated against a written standard before and after deployment. An agent with no guardrails and no evaluation is a liability with an API key.
What can AI agents do reliably in 2026?
Reliably: pull and summarize from your own data, draft for human review, triage and route, reconcile records across systems, monitor and flag, and run multi-step workflows with checkpoints. Still unreliable: fully autonomous high-stakes actions with no human gate. Good agent design puts the human approval exactly where the risk is, and we'll tell you which side of that line each use case sits on.
How do you keep an AI agent from making things up?
Ground it, guard it, grade it. Grounding means the agent answers from your documents and systems, with citations back to the source. Guarding means bounded tools, deterministic rules for anything consequential, and human approval gates on risky actions. Grading means an evaluation suite that tests the agent against known cases before deployment and keeps watching it after. None of this gets made-up answers to zero, which is why the gates and the monitoring stay on after launch.
Can agents integrate with the tools we already use?
That's the point. Agents earn their keep inside the stack you already have (email, Slack, CRMs, ticketing, accounting, custom databases and APIs), and a separate app your team has to remember to open defeats the purpose. The integration scope is written down: which systems, which permissions, which actions need a human, and what gets logged.
Automation you can audit.
Tell us which hours your team keeps losing. We'll reply with a reading of what an agent can take off their plate, and what it shouldn't touch.
100% in-house development · Oregon & California, USA · 25+ years building production systems
grounded · guarded · graded · human gates where the risk lives · privacy ·
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