Our approach
One workflow. In production in about three months.
Large firms sell multi-year transformations. We start with one workflow that matters, prove it in production, then scale what works.
TODO: Week-by-week timeline not confirmed; we only claim “3 months to production”
Weeks 1–2
Discover
Pick the workflow and map the data sources it depends on.
Weeks 3–4
Design
Decide what the agent reads, what it may do, and where people stay in the loop.
Weeks 5–12
Deploy
Connect the data, build the agent and put it into production in your environment.
Then
Scale
Measure the results and extend to the next workflow and the next team.
The problem
Everyone has AI. Few have results.
Most companies bought a chat tool and ran a few pilots. Then progress stalled. The research is consistent about why: they added AI to individual tasks, on top of data it couldn’t reach.
The fix is to redesign one workflow end to end, connect it to the data that drives it, and let an agent run it.
- 80%+
of companies report no bottom-line impact from their AI investments yet.
- 23%
are scaling an AI agent anywhere in the business. No more than 10% are doing it in any single function.
- 3×
Companies getting real value are about three times as likely to have redesigned whole workflows, not just tasks.
Agentic AI
We’ve built more agents than we can count.
Each one is designed around a real workflow, wired into the systems that workflow touches, and measured on the hours it gives back.
Human in the loop
The agent does the work. A person approves it.
Right for drafts, decisions and anything customer-facing. The agent prepares; your team signs off.
Human above the loop
The agent runs the process. A person handles exceptions.
Right for high-volume, rules-based work. Your team sets the rules and steps in only when the agent flags something.
TODO: Two-week Agent Readiness Assessment not confirmed. Approve or cut
Start here
Agent Readiness Assessment
A two-week, fixed-scope review with our senior team. You come away knowing which workflow to automate first and what it will take.
- Workflow shortlist. The three processes where an agent would return the most time.
- Data readiness check. Which sources the agent needs, and whether they’re ready.
- Agent design. What it reads, what it does, and where people approve.
- Business case. Expected hours saved, cost and timeline to production.
- Governance plan. Permissions, audit and security for your environment.
Results
What happens when AI is built on the right data.
- 85%
- user adoption rate
- 40%
- reduction in manual research
- 3 mo
- to production
- 24/7
- global availability
Start a conversation
Which workflow should your first agent take on?
Bring us one process and the systems behind it. We’ll show you what an agent could do with it.
Schedule a conversationAbout the assessment
TODO: Scheduling link or email for this button
TODO: “About the assessment” goes with the unconfirmed assessment