Solutions
AI Agents
For leadership teams who have seen plenty of agent demos and want one that does a real job in their business. We build agents that work inside the systems you already run and ask before they act.
You're likely a fit if…
The demos never looked like your business.
Vendors show agents booking meetings. Nobody has shown you which job, in which department, an agent could actually take on.
Work waits in queues for rule-following steps.
Look up the account, check the order, draft the reply, open the ticket. Skilled people spend their day on handoffs.
Problems surface by accident.
A late shipment pattern or an account going quiet gets noticed when a customer calls, not when the data first showed it.
Your last pilot couldn't be trusted with real actions.
It answered questions well enough, but nobody would let it touch a live record.
What we build
Conversational data agents
Staff ask in plain English and get answers from live business data, with the query and source shown. The agent can open a request on someone's behalf.
Learn more: Conversational data agentsProactive monitoring agents
Agents that read your ERP, order and CRM data on a schedule and send the right person an exception, with the evidence attached.
Task agents with approval steps
The agent drafts the record update, the order change or the customer reply. A person approves before anything is written.
Tool access, permissions and logs
The connectors, scoped service accounts and audit trail that let an agent read and act only where you've allowed it.
AI Security: Tool access, permissions and logs
Scope
Included, and not
One agent for one defined job, connected to the systems it needs, with tests on real cases, logging, approvals and documentation. Not included: replacing core systems, or broad-access agents built to see what happens.
What we need from you
An owner for the agent's job, early access to test or read-only data, and short sessions with the people who do the work today.
Access and approvals
Each agent has its own credentials and read-only access by default. Write access is added only where its job needs it, behind an approval step.
What drives cost
How many systems the agent reads and writes, how accessible the data is, how many actions need approval flows, and how many teams use it. Builds are scoped and priced after the assessment.
How we'd start
Start with an Assessment to find the jobs where an agent earns its place, and size each one.
Pick one job. Agree the outcome, the users, the systems and the measure, and baseline how the work runs today.
Build in short cycles with the people who'll use it, on your real data.
Ship with tests, logs and approval steps, and measure the work against the baseline.
Hand over to your named owner. You keep the code, prompts and configuration; we stay involved only if you want us to.
Common questions
What's the difference between an agent and a chatbot?
A chatbot answers. An agent can also take steps, like checking two systems, drafting a change or opening a request, within permissions you set. Ours ask a person before anything changes a record, sends a message or spends money.
What happens when the agent gets something wrong?
Every answer carries its evidence, so mistakes are visible. Tests on the cases that matter run on every change, and each miss becomes a new test.
Who owns the agent afterward?
You do. A named owner in your business has it from day one, with the documentation and tests to keep it working after we step back.
How long does a first agent take?
Most first agents size as S (1–3 weeks) or M (1–2 months) in the Assessment. An agent that spans several departments is usually L (3–6 months), and we'd deliver it in stages.
Industries where this applies
Let's find where AI pays off in your business.
Thirty minutes with Daniel. No pitch deck: you talk about your business, I tell you honestly where AI fits and where it doesn't.