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Enterprise AI agents that do the work

Autonomous, tool-using agents connected to your systems, governed by guardrails and human approvals, and built to run in production rather than in a demo.

How an agent works

Plan. Act. Verify. Improve.

1

Trigger

Email, ticket, event or schedule

2

Reason & plan

LLM breaks the goal into steps

3

Act with tools

APIs, databases, apps, browsers

4

Verify & approve

Guardrails + human sign-off

5

Learn

Logged, evaluated, improved

Use cases

Where agents pay off first

Customer support agent

Resolves common tickets, drafts replies, and escalates with full context.

Sales & lead research

Enriches leads, personalizes outreach and keeps your CRM current.

Finance & ops agent

Classifies, reconciles, chases approvals and prepares reports for review.

HR & recruiting agent

Screens, schedules and answers employee questions with human approval.

IT & helpdesk agent

Handles routine access and device requests and triages incidents.

Knowledge assistant

Answers internal questions with citations from your own documents.

Document processing

Extracts, validates and routes data from invoices, contracts and forms.

Compliance & monitoring

Watches for policy exceptions and prepares evidence for audits.

Engineering standards

Enterprise-grade, not experimental

Security firstLeast-privilege access, SSO, secrets management, VPC or on-prem options.
GuardrailsPolicy checks, approval gates and spend limits on every action.
ObservabilityFull traces, audit logs and quality evaluations in production.
Model-agnosticOpenAI, Anthropic, Google or open-source, chosen per use case.

Engagement model

From pilot to production

  1. 1

    Opportunity map

    Identify and rank the workflows where an agent delivers the clearest return.

  2. 2

    Pilot

    Build one agent on real data with evaluation tests and a defined success metric.

  3. 3

    Harden

    Add guardrails, approvals, monitoring and security review before wider rollout.

  4. 4

    Scale

    Expand to more workflows with ongoing operations and optimization.

FAQ

Agents, answered

What is the difference between an agent and a chatbot?

A chatbot answers. An agent plans multi-step work, uses tools such as your CRM or ticketing system, and takes actions, under rules and approvals you define.

Will agents replace my team?

Our designs keep people in control: agents handle repetitive work and escalate edge cases and sensitive decisions to humans.

Where does our data go?

You choose: your cloud, a private VPC or on-prem where required. We apply least-privilege access and can work under NDA.

How quickly can we see a first agent?

A scoped pilot typically reaches a working first workflow in weeks, depending on integrations and data access.

Let us map your first agent

Book a call and we will outline the workflows worth automating first.