Production agents your enterprise can actually deploy.
Most agents are demos. Autonomous Agents are systems — scoped to a specific job, trained on your context, integrated into your tools, and bounded by a human approval gate on every material action. Built to survive compliance review, not just a sales call.
Discovery call → scoped role + guardrails → first agent live in 4–6 weeks.
Built for operations, revenue, and support leaders at growing companies who need leverage from AI that passes legal, security, and audit review.
Deployed in your cloud · 20+ years engineering leadership · Human-in-the-loop by default
Why enterprise agent pilots stall.
Four reasons agents get stuck in the demo phase inside growing companies.
Pilots never reach production
Your team has run demos for months. Nothing is actually operating in the business. Leadership wants leverage; you have screenshots.
Generic agents are a liability
Off-the-shelf agents hallucinate, break SLAs, and expose data. Procurement, legal, and security block anything you cannot control.
Your context is scattered
CRM, docs, email, Slack, tickets, tribal knowledge. An agent with no context produces generic output — which is worse than no output.
Humans stay in the loop forever
You do not want an autonomous AI. You want an agent that drafts, analyzes, and queues — so humans can focus on judgement.
What an Enterprise Agent engagement delivers
One agent, scoped to one high-value job. Trained on your context. Deployed in your tools. Every material action gated by a human.
- Agent scoped to a single operational role (ops, sales, CS, support, finance ops)
- Trained on your data, playbooks, and past decisions — via the context engineering layer
- Operates inside your existing tools (Slack, email, CRM, ticketing, BI, internal apps)
- Human approval required for every customer-facing or irreversible action
- Evaluation dashboard: what the agent drafted, what humans approved, what changed
- Deployed in your cloud with SOC 2-ready audit logging from day one
Scope before we sell you anything.
Free first steps before you commit.
Discovery call
Walk through where the team is most bottlenecked, which job would pay back fastest, and what compliance boundaries the agent has to live inside.
A prioritized list of candidate agent jobs with rough ROI.
Role + guardrails scope
Two-week scoping: what the agent will draft, decide, and execute; what always requires a human; what data it needs access to; what success looks like.
A role charter your legal and security teams can sign off on.
Build and go live
Agent built, integrated with your context layer, and evaluated against your standard. Weekly calibration with the business owner until outputs match. Ships live with full human-in-the-loop approval.
A production agent operating inside your business, not on a slide.
What an Autonomous Agent looks like in production.
Mid-market B2B SaaS, 220 employees
The problem
Customer success team was drowning in manual renewal-prep work. Each CSM was spending 6+ hours per renewal pulling data from CRM, usage logs, support tickets, and calls. Two prior 'AI copilot' pilots had stalled — neither produced outputs the team trusted.
The outcome
Enterprise Agent scoped to renewal briefs: pulls usage, health, support history, and call context into a one-page brief the CSM reviews and approves. Approved briefs auto-populate the renewal playbook. Human signs every outbound.
Which operational job would pay back fastest if an agent handled it tomorrow?
Scope your first agentCommon questions
How is this different from off-the-shelf agent platforms?
Those ship horizontal capabilities; you still have to scope the job, wire the context, and build the guardrails. We do that for you, for one specific role, to a production standard your compliance team will actually approve.
Is this an autonomous agent?
No. Every material action has a human approval gate. The agent drafts, analyzes, queues, prepares — the human reviews and decides. We do not build systems that act unilaterally on customers, money, or regulated data.
Which operational roles fit best?
Renewal prep, account research, proposal drafting, support triage, ops reporting, finance reconciliation prep, internal-knowledge lookup. The scoping call narrows to the role with the best payback in your business.
What does it cost?
First agent runs $200–400k, fixed price, for a 4–6 week build. Additional agents sharing the same context layer are typically 30–50% cheaper due to shared infrastructure.
Where does it run?
Your cloud (AWS, GCP, or Azure). Your data, your auth, your perimeter. The agent is a private deployment, not a shared SaaS.
Compliance and audit?
Every agent action is logged — input, reasoning, output, approver, timestamp. SOC 2-ready audit trail. We've deployed under enterprise and regulated environments.
Is this the right fit?
Good fit
- Team has a repeatable, high-volume job costing senior-person hours
- Pilots have stalled and you need something that actually ships
- Compliance, legal, or security blocks generic AI tools today
- Comfortable with human-in-the-loop — you do not want a fully autonomous agent
Not a fit
- Looking for a fully autonomous AI (we do not build those)
- One-off experimentation without a sponsor or a real operational job to solve
- Budget below ~$150k
- No appetite for putting a system into production alongside humans
Which operational job would pay back fastest if an agent handled it tomorrow?
30 minutes with a CTO. Bring the operational job you wish was already automated — and what has stopped you.