AI agents that do the work, not just talk about it.
A chatbot answers questions. An agent gets things done. It reads the request, decides on the steps, uses your systems, and either completes the task or hands it to a person for approval. We build agents like that, for real business processes, with guardrails included.
Connected to your systems. Supervised by your people.
Each agent we build has a clear job, a defined set of tools it's allowed to use, and checkpoints where a person reviews its work.
- Trigger: an email, form, ticket, phone call, file upload or schedule kicks it off.
- Reason: the AI model understands the request and plans the steps.
- Act: it uses approved tools such as your CRM, Microsoft 365, EMR or database.
- Check: sensitive actions pause for human approval.
- Log: every decision and action is recorded for review.
Start with the work your team dreads.
These are the kinds of agents that tend to pay off fastest for small and mid-sized businesses. Every build is tailored to your process and your systems.
Customer service & intake
Answers questions from your knowledge base, qualifies requests, books appointments and creates tickets or CRM records. It works on your website, by email or by text.
Document processing
Reads invoices, claims, applications and contracts. It pulls out the key data, checks it against your rules, and routes exceptions to the right person.
IT help desk
Handles tier-1 requests like password resets, access requests, software installs and how-to questions, and escalates anything bigger to our technicians.
Sales & CRM
Researches leads, drafts personalized follow-ups for your approval, logs activity and keeps your pipeline clean, so your salespeople spend their time selling.
Internal knowledge assistant
Gives your staff instant answers from your SOPs, policies and SharePoint, with sources cited. It respects existing permissions, so people only see what they're allowed to.
Operations & reporting
Pulls data from several systems, reconciles it, and delivers the weekly report or alert your managers currently build by hand.
Every agent ships with guardrails.
An agent that can take actions needs the same oversight as a new employee, and in some ways more. These controls come standard, not as add-ons.
How we govern AILeast-privilege access
Each agent gets its own identity and only the permissions its job requires.
Human-in-the-loop
Payments, deletions, external messages and other sensitive actions wait for a person to approve them.
Full audit trail
Every prompt, decision and tool call is logged and reviewable.
Tested before launch
We run evaluations for accuracy, edge cases, prompt injection and data leakage before go-live.
Data stays protected
We use enterprise AI services configured so your data isn't used to train public models.
Cost limits & kill switch
Usage caps, alerts, and a way to pause any agent instantly.
From idea to agent in production.
Discover
We map the process, the systems involved and what success looks like.
Design
We define the agent's job, tools, approval points and risk controls.
Build
We develop and connect the agent to your real systems in a safe test environment.
Evaluate
We test against real-world scenarios, edge cases and security attacks.
Launch
We roll out in stages, train your team, and document everything.
Operate
We monitor, tune and report on performance every month.
Start small. Scale what works.
Agent Pilot
One focused agent for one process, built and tested with a small group, so you can measure the value before you commit further.
- Discovery & design
- Working agent in a controlled rollout
- Results review & next-step plan
Production Build
A production-ready agent, or a team of agents, fully integrated, governed and documented.
- Integrations with your systems
- Guardrails, evals & audit logging
- Staff training & runbooks
Managed AgentOps
We run your agents like we run your IT: monitored, updated, secured and improved every month.
- Monitoring & incident response
- Model and prompt updates
- Monthly performance reports
Questions we hear a lot.
What's the difference between a chatbot and an AI agent?
A chatbot answers questions. An agent can take actions such as looking up records, updating systems, sending drafts for approval and completing multi-step tasks within the limits you set.
Will our data be used to train AI models?
No. We build on enterprise AI services, configured so your prompts and data aren't used to train public models, and we apply your existing access controls.
Do we need Microsoft 365 Copilot?
Not necessarily. Some agents work best in Copilot Studio, and others are better as standalone builds. We recommend whatever fits your systems and budget.
What if the agent makes a mistake?
That's why we design approval points, logging and testing into every agent. High-impact actions need a person's sign-off, and every action can be traced and reversed.
How much does it cost?
It depends on scope and integrations. After a short discovery call, we'll give you a clear quote. Most clients start with a pilot.
Which process would you hand to an agent first?
Book a free 30-minute consultation. We'll tell you honestly whether an agent is the right fit.