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Autonomous Agents

Delegation,
not just automation.

Goal-driven AI agents that run multi-step business work — assembling quote packages, drafting vendor outreach, classifying documents, administering projects — under supervision you control.

Multi-step task execution Approval gates by default Every action logged
task board — a sample day
approval gates on all actions logged
Queued2
Classify inbox attachments
queued · 38 documents · rules v3
Chase overdue status updates
queued · 5 owners to nudge
Working1
Vendor outreach — RFQ-2215
step 1 of 3 · drafting
Needs review1
Cover email — RFQ-2214
held · awaiting your approval
Done2
Quote package — RFQ-2214
done · staged v1 · log #118
Weekly status summary
done 09:00 · log #117
Capabilities

Hand it a goal.
It runs the steps.

Each agent is configured for one job — with the system access that job requires and nothing more. These are the assignments where agents earn their keep.

Quote & proposal packages

The agent assembles the whole package — pricing pulled from your sheets, terms from your templates, cover letter drafted — then stages it for your review, not your assembly.

RFQ generation & vendor outreach

Give it a bill of materials; get back drafted RFQs and vendor emails, tailored per recipient, held in the outbox until you approve them.

Classification & filing at scale

Hundreds of inbox attachments sorted, named by your convention, and filed to the right folder and record — the backlog nobody was ever going to clear by hand.

Project administration

Status chasing, checklist upkeep, deadline reminders. The agent notices what has gone stale and nudges the right person before you have to.

Research & summarization runs

Point it at a question — vendor options, policy changes, published pricing — and get a structured summary with sources, instead of forty open tabs.

Multi-system tasks

Through API integrations, one agent can read your CRM, update your project tool, and write the spreadsheet — the swivel-chair work between systems.

Supervision is the feature

Autonomous, not unsupervised.

"Autonomous" should make an ops lead nervous. So we build the controls first: you decide what an agent may touch, and outbound work waits for a human until you — not we — decide it should not. Every run also feeds our AI operations monitoring.

Approval gates

Nothing leaves the building on its own. Emails, quotes, and filings hold for sign-off until you deliberately loosen the gate.

Full action logs

Every step is recorded — inputs, outputs, timestamps. Replay any run and see exactly what the agent did and why.

Scoped permissions

Each agent gets the minimum access its job requires. New folders, new systems, new actions — each one is a grant, not a default.

Kill switch

Pause or stop any agent instantly. In-flight work holds where it is; nothing half-finished goes out the door.

Our Responsible AI commitments
Where agents fit

Agents don't work alone.

An agent is the worker. The rest of our AI stack supplies its facts, its paperwork skills, its rails, and a secure place to live.

Knowledge Intelligence — the facts

Agents answer from your indexed records — prior quotes, specs, project history — instead of improvising from memory.

Explore Knowledge Intelligence

Document Intelligence — the paperwork

Extraction, classification, and reconciliation give agents clean structured data to act on, not raw PDFs.

Explore Document Intelligence

Workflow Automation — the rails

Triggers, queues, retries, and integrations — the plumbing agents run on and report through.

Explore Workflow Automation

Secure AI Hosting — the home

Agents deploy on our own GPU-accelerated infrastructure with private endpoints and access controls.

Explore Secure AI Hosting

Agents are built on commercially available foundation models from established providers, including OpenAI — then scoped, configured, and reviewed for your specific business use case. The model is a component; the controls are the product.

Questions

The questions everyone asks

What stops an agent from going rogue?
Three controls, layered. Scoped permissions mean an agent can only touch the folders, systems, and actions you granted — there is no "everything" mode. Approval gates hold outbound work — emails, quotes, filings — for human sign-off. And every step is logged, so behavior is fully auditable. If anything looks wrong, the kill switch stops the agent instantly.
Which tasks fit agents best?
Repeatable work you could describe as rules: when something arrives looking like X, do Y, and flag anything unusual. High-volume, low-ambiguity tasks — package assembly, filing, status chasing, drafting — are ideal. One-off judgment calls are not; those stay with your people.
What happens when an agent makes a mistake?
Outbound mistakes get caught at the review gate — nothing sends without approval until you loosen that setting yourself. Runtime errors and low-confidence steps route to a human queue with the full run log attached, so whoever picks the task up sees exactly what happened and where.
Is this about replacing staff?
It is about the backlog. Agents take the repetitive work that never gets done — the filing, the chasing, the package assembly — so your people spend their time on judgment calls, relationships, and exceptions. Approval authority stays human, on purpose.
Autonomous agents

Write the job description. We'll build the agent.

Brief us the way you would brief a new hire — the inputs, the steps, what finished looks like. You'll get back a scoped plan: the agent, its permissions, its gates, and its rollout.