How we build and operate your AI Employees.
A structured four-phase process from discovery to ongoing improvement — built for real business outcomes, not theoretical demos.
Discovery & analysis
We audit how the department actually works — tools, handoffs, decision points — and rank where an agent has the biggest lever. Your processes, not a generic template.
Architecture
We design the agent system: which data it reads, which tools it can act in, where it escalates to a human, and how success gets measured.
Build & training
We build the agents and train them on your data, processes and language. Every action is traceable, so you can see exactly what the agent did and why.
Operate & improve
We run the agents and keep developing them. Agent-as-a-service — not a one-off project handover with a manual attached.
What happens in each phase.
Discovery
Every engagement begins with a structured discovery phase. We conduct a workshop with your department heads and key stakeholders to map out current workflows, identify bottlenecks, and document the decision points and data sources involved in each process. We also audit your existing tool stack — CRM, helpdesk, ERP, calendars, document storage — to understand what APIs and data formats the agents will need to work with.
- Identify 3–5 high-impact workflows per department that are candidates for automation
- Map data sources, tool permissions, and security requirements
- Define success metrics and baseline current performance (time spent, error rates, throughput)
- Typical timeframe: 3–5 business days
Agent Architecture Design
Based on the discovery findings, we produce a detailed architecture document for each AI Employee. This specifies which tools the agent connects to, how it reasons through each workflow, which decisions it can make autonomously versus escalate to a human, and how its performance is measured. The architecture is reviewed and signed off by your team before any code is written.
- Select the appropriate AI model and reasoning framework for each agent's domain
- Design tool integrations and data flow diagrams
- Define escalation rules, confidence thresholds, and human-in-the-loop handoffs
- Typical timeframe: 3–5 business days
Build & Integrate
Each agent is built iteratively in two-week sprints. We connect the agent to your existing tools, configure its knowledge base from your documentation and historical data, and run it against real scenarios from your team. Every integration is tested for correctness, latency, and edge cases before the agent is deployed to a staging environment for user acceptance testing.
- Concurrent build sprints for each AI Employee in the engagement
- Real-data testing using anonymized or sandboxed versions of your tools
- User acceptance testing with a small group of your team members
- Typical timeframe: 2–4 weeks depending on number of agents and integration complexity
Operate & Iterate
Go-live is not the finish line. We monitor every agent's performance continuously, track resolution rates and time saved against the baselines established in discovery, and ship improvements on a weekly cycle. As your business processes evolve, we update agent configurations, add new tool integrations, and retrain on fresh data — all without any engineering work on your side.
- Weekly performance reviews and improvement deployments
- Real-time dashboard showing agent metrics and ROI per department
- Quarterly business reviews with your leadership team
- No handoff, no vendor lock-in — full visibility into how every agent operates