AI & intelligent automation
AI that does real work inside your business rules
We implement AI tools, build AI-powered applications and agents, and automate repetitive processes, connected to the systems and data you already use, with people approving the decisions that matter.
- AI agents
- Process automation
- System integration
- Human approval & audit trail
What we build
Four ways to put AI to work
AI tool implementation
Select, configure and roll out AI tools for your teams, with guidance on where they help and where they don't.
AI-powered applications
Add AI features to your product: summarization, classification, search, drafting and assistants for your users.
AI agents
Agents that take a request or event, look up data, apply your rules, and carry out a defined set of actions.
Intelligent workflows
Automate multi-step business processes that currently rely on email, spreadsheets and copy-paste.
How an AI agent works
Every step is defined, logged and reviewable
An agent is only as good as the rules and data it has. We design each one around a specific job, the systems it may touch, and the points where a person signs off.
- STEP 1User or eventRequest, email, new record
- STEP 2AI agentUnderstands the task
- STEP 3Data + business rulesLooks up, checks limits
- STEP 4DecisionProposes an outcome
- STEP 5Automated actionUpdates systems, notifies
- STEP 6ResultLogged and reported
Select a step to see what happens there.
Example agent run
Engagement intake, from request to approved staffing
An illustrative agent for a professional-services firm: a new engagement arrives and the agent prepares a staffing proposal for a manager to approve.
- Connects to the scheduling engine instead of guessing availability
- Stops for approval before anything is committed
- Writes every step to an audit log
- 09:02:14 Received request: “New audit engagement, fieldwork starts Nov 2, needs 1 manager + 2 seniors.”
- 09:02:16 Checked rules: independence list clear · budget cap 420 hrs · manager approval required
- 09:02:19 Queried scheduling engine: 3 qualified seniors under 85% utilization for Nov 2–20
- 09:02:21 Proposed team: Grace L. (Mgr), Maya R., Hannah T. · est. 396 hrs
- 09:02:22 Sent to engagement partner for approval · waiting
- 10:15:03 Approved · schedule updated · team notified by email
Where automation fits
Good candidates for AI automation
Examples of repetitive work we look for when assessing a process. The right starting point depends on your data and systems.
Request and email intake
Read incoming requests, extract the details and create the right record or task.
Data entry and reconciliation
Move data between spreadsheets and systems, and flag mismatches for review.
Document drafting
Draft summaries, reports and routine correspondence from structured data for a person to finalize.
Routing and follow-up
Send work to the right person based on rules, and remind them before it's late.
Scheduling assistance
Answer “who's available?” questions using live data from the optimization engine.
Reporting questions
Let managers ask plain-language questions of approved reporting data.
Responsible by design
Realistic about what AI should do
AI agents are useful for well-defined work. They are not a replacement for judgment on decisions that affect clients, people or money. We design for that.
- Scoped permissions. Each agent can reach only the systems and actions its job needs.
- Human approval. Sensitive or irreversible actions wait for a person.
- Audit trail. Inputs, reasoning summary, actions and approvals are logged.
- Fallbacks. When confidence is low or data is missing, the agent hands off instead of guessing.
- Measured results. We agree on what to measure (time saved, error rate, turnaround) before rollout.
Which process would you automate first?
Tell us where your team loses the most time. We'll assess whether AI is the right tool and what a first agent would look like.