Custom AI Copilot Development for Teams
AI assistants built for your team, trained on your context.
Why this service
Generic AI tools don't know your processes, terminology or customers. A custom copilot is built on top of your team's context — it understands internal practices and respects your security boundary.
What you concretely get
Every phase of the engagement produces a written or systemic deliverable. No slide-deck show, no promised "later".
Discovery report
Current state, bottlenecks, baseline metrics and a concrete proposed focus. 12–18 pages, written.
Architecture diagram
Technical design: model choices, data flow, integration points, security. Readable and reviewable.
Working production system
Deployed system in your environment — not a demo. Source code and configurations are handed over.
Runbook and documentation
User guide, maintenance procedures, failure-mode checklist, escalation paths. Finnish/English.
Adoption programme
User training per role, internal "AI champion" coaching, 30/60/90-day milestones.
Outcome reports
Monthly: where metrics have moved against the baseline, what adjustments come next month.
How we measure success
Metrics are agreed at discovery and the baseline is captured before implementation. These are the numbers we discuss at the 30/60/90-day check-ins.
- Time per user task
- Weekly active usage (DAU/WAU)
- User-rated output quality
- Scenario success rate
- Expert-escalation count
- Adoption depth — % of tasks where the copilot is actually opened
Use cases
Sales copilot
Drafts proposals, updates the CRM and suggests next actions.
HR copilot
Answers employee questions on leave, benefits and policy.
Marketing copilot
Campaign drafts, social posts and creative briefs.
Finance copilot
Explains variances and drafts management summaries.
Engineering copilot
Reviews code against your team's conventions.
Operations copilot
Helps with tickets, support cases and escalations.
Our delivery process
Discovery
We map the current state, processes and biggest productivity leaks.
Use case selection
We prioritise the highest-value, lowest-risk combinations.
Pilot
We build a working version in 4–6 weeks, with metrics.
Roll-out
We harden it for production and integrate the SaaS stack.
Training
Hands-on workshops and an internal champion for the team.
Optimisation
We measure, tune and scale — AI keeps living.
Technologies used
Frequently asked questions
A typical pilot completes in 4–6 weeks, with full production use in 2–3 months. We give a concrete timeline after the discovery call.
We design the architecture so your data stays under your control. We support self-hosted models and EU-region cloud, GDPR-aligned.
No. We build on top of your existing SaaS stack — we connect them, we don't replace them.
Adoption is part of every engagement. Without it, AI doesn't produce results — and that's already priced in.
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Learn more →Ready to get this in production?
We always start with a free 30-minute discovery call. No sales pressure.
Book the discovery call →