Agents that run while your team sleeps.
We build production AI agents for sales, customer support, and workflow automation. Eval-hardened, observable, and delivered in 2–6 weeks. Not demos — systems that replace real human hours with measurable ROI.
WHAT IS AN AI AGENT?An AI agent is a software system that perceives its environment, makes decisions, and takes autonomous action across multiple tools to complete multi-step tasks — without step-by-step human instruction. Unlike chatbots that respond to prompts, agents execute full workflows: qualifying a lead, updating a CRM, sending a follow-up, and closing the ticket — start to finish, without human touch. We build production agents for sales, customer support, and back-office workflows, delivered in 2–6 weeks.
Why agents, why now.
The adoption curve is already steep. The companies building agents today will have an operational advantage that compounds for years.
The agent stack.
Six agent types. Each one production-proven, eval-hardened, and built to hand off gracefully when a human needs to step in.
Sales Agent
Finds qualified leads, enriches contact data, writes personalised outreach, and books meetings — without a human in the loop.
Support Agent
Answers tickets in your brand voice, handles returns, looks up order status, and escalates edge cases to humans instantly.
Workflow Agent
Orchestrates multi-step internal processes — data sync, approvals, reporting — replacing brittle scripts with observable agent graphs.
Voice Agent
Handles inbound calls, qualifies prospects, manages scheduling, and processes returns — all with a natural, on-brand voice.
Research Agent
Produces competitor briefs, due diligence reports, and market scans on demand — replacing hours of manual research with minutes.
Ops Agent
Watches dashboards 24/7, flags anomalies before they become incidents, drafts runbooks, and pages the right person automatically.
How we build.
Four stages. No surprises. You see progress in week one.
Scope & Eval
Define the agent's job in precise terms. Write the eval set — the test cases it must pass before we ship. Baseline the current human cost.
Build
LangGraph or n8n graph, tool integrations, memory layer, guardrails, and full observability so you can see every decision the agent makes.
Hardening
Eval pass rate >90%. Red-team for edge cases. Escape-hatch handoff to humans. Cost ceilings enforced. No surprises in production.
Deploy
Production deploy with CI pipeline, written runbook, on-call escalation paths, and 30-day support. You own it. We document everything.
What a production agent trace looks like.
Real trace from a support agent handling a billing refund request. 4.8 seconds start to finish.
Pricing and readiness signals.
What does it cost?
- Single-purpose agent$8k – $18k
One job. One integration. Fully eval-hardened. - Multi-tool agent$18k – $35k
Three to six tool integrations. Complex routing logic. - Multi-agent system$35k – $60k
Orchestrator + specialist agents. Full eval suite. - Voice add-on+$8k
Adds voice I/O to any agent above.
Final scope confirmed after the free Signal Audit.
You're ready if:
- You have a repetitive task that currently takes a human 2+ hours per week
- You have clear success/failure criteria — you know what "good" looks like
- You have access to the tools and APIs the agent will need to connect to
- You want a measurable ROI, not just a demo that impresses people
The questions everyone asks first.
Custom agents are built around your specific workflow, your data, and your guardrails. No-code tools build generic automations. We build agents that can make multi-step decisions, call multiple tools in sequence, handle errors gracefully, and hand off to humans when appropriate. They pass an eval suite before they touch production.
Every agent we build has an escape-hatch handoff — a defined condition under which it pauses and escalates to a human. We also set cost ceilings and action limits so a runaway agent can't cause damage. The eval harness catches the most common failure modes before deployment.
We select the best model for each task — often that's a smaller, faster, cheaper model rather than GPT-4 Turbo. We support OpenAI, Anthropic, Google, and open-weight models via Ollama or Replicate. If you have a preferred vendor or compliance requirement, we'll build around it.
Single-purpose agents: 2–3 weeks. Multi-tool agents: 3–5 weeks. Multi-agent systems: 5–8 weeks. These timelines assume you can provide access to APIs and test data within 48 hours of kickoff. Delays in access are the single most common cause of overruns.
API credentials or sandbox access for the tools the agent will connect to, a description of the current human workflow, 20–50 example inputs and expected outputs for eval set construction, and a point of contact who can answer questions about edge cases. That's it.