Methodology · 04 PHASES · STAGED COMMITMENT
Four phases. A deliverable at the end of each one.
Discovery to production in fixed scopes. You see evidence before each new commitment, and you can stop after any phase and keep the work.
The four phases · OVERVIEW
Audit & Discovery
We map your systems and data, and find the highest-leverage places to put AI to work.
You keepAn opportunity map and a fixed-scope proposal.
Prototype
A proof of concept built against your real data (not a slide deck) to validate feasibility and ROI.
You keepA working prototype and an honest go/no-go readout.
Implementation
Production engineering: integration, pipelines, evals, monitoring, and security review.
You keepA system in production, documented and observable.
Scale & Optimize
Continuous tuning as your data and business change, plus training so your team can run it.
You keepDashboards, runbooks, and a team that owns it.
Phase 01 · Audit & Discovery · 1–2 WEEKS
First, we learn how your business actually runs.
Every engagement starts with an audit of your systems, data, and workflows. We interview the people who do the work, trace where the hours go, and find the places where AI pays for itself fastest.
The output is not a vision deck. It is a prioritized opportunity map with feasibility notes, ROI estimates, and a fixed-scope proposal for the first build.
Activities
- A.1Infrastructure & data asset audit
- A.2Stakeholder interviews & workflow analysis
- A.3Opportunity identification & prioritization
- A.4Technical feasibility assessment
- A.5ROI projections & business case
- A.6Roadmap with milestones & executive briefing
You keepAn opportunity map and a fixed-scope proposal, useful even if we never speak again.
Phase 02 · Prototype · 2–4 WEEKS
Proof on your real data, before any real money.
We build a working proof of concept against your actual data: not a demo dataset, not a slide deck. Candidate models are benchmarked for accuracy, latency, and cost at scale.
Success criteria are agreed up front. If the prototype clears them, you have the evidence to fund production. If it does not, you walk away having spent a fraction of a full build.
Activities
- B.1Working proof of concept on your data
- B.2Model selection & benchmarking
- B.3Accuracy & performance evaluation
- B.4Cost projections at scale
- B.5User testing & feedback integration
- B.6Go/no-go readout against agreed criteria
You keepThe prototype, the benchmark report, and an honest go/no-go readout.
Phase 03 · Implementation · 6–12 WEEKS
Engineering that survives security review.
The validated prototype becomes a production system: model integration, data pipelines, secured APIs, and wiring into the systems you already run, such as ERP, CRM, warehouse, and support desk.
We ship with CI/CD, comprehensive testing, and staged rollouts that keep your operations running. Evals, monitoring, encryption, role-based access, and audit logging are built in, along with the documentation your security and compliance teams will ask for.
Activities
- C.1Production model deployment & fine-tuning
- C.2Data pipelines & ETL workflows
- C.3Secure API endpoints & access control
- C.4System integrations · ERP, CRM, data warehouse
- C.5Evals, load testing & monitoring
- C.6Security review, audit logging & documentation
You keepA system in production: documented, observable, and owned by you.
Phase 04 · Scale & Optimize · ONGOING
Kept sharp as your data and business change.
AI systems are not set-and-forget. Models drift as data changes, so we monitor for it, retrain when needed, and tune for cost as usage grows, before any of it shows up in your numbers.
Support runs at the level you choose: monitoring-only dashboards, managed operations, or full AI operations. Either way, we train your team so the system never depends on us.
Activities
- D.1System monitoring & alerting
- D.2Model drift detection & retraining
- D.3Performance & cost optimization
- D.4Quarterly business reviews
- D.5New feature development
- D.6Team training & handover
You keepDashboards, runbooks, and a team trained to run it without us.
Why it works · 03 PRINCIPLES
Built to de-risk, not to bill hours.
The methodology exists to answer one question early and cheaply (is this worth doing?) and then to ship it properly.
Staged commitment
Each phase is fixed-scope with its own go/no-go gate. You never fund the next step on faith, only on evidence from the last one, and you can stop at any gate.
Outcomes, not outputs
Every phase carries business metrics, not activity reports. We prioritize the highest-impact opportunities and measure success in hours saved and tickets resolved.
No dependency
Documentation, training, and collaborative development from day one. Your team can maintain and extend the system after we leave.
FAQ · 04