A proven, collaborative methodology from discovery to deployment—and beyond.
We've refined this approach across dozens of automation and AI projects. It balances speed with thoroughness, delivers early value, and ensures your team can maintain what we build.
Understand your processes, pain points, and priorities
Architect the solution with security, cost, and maintainability in mind
Develop in sprints with continuous testing and feedback
Deploy, monitor, document, and optionally manage ongoing
Duration: 1–3 weeks
Discovery is about understanding your current state, identifying the real problem, and defining success criteria. We don't start building until we've mapped your workflows, understood your data, and confirmed the business case.
We talk to the people doing the work—not just leadership. We need to understand the day-to-day pain points.
Current-state workflow diagrams showing bottlenecks, handoffs, and inefficiencies.
What systems hold your data? What APIs exist? What permissions are needed?
Not everything needs automation. We rank opportunities by impact, effort, and ROI.
Data handling requirements, compliance obligations, approval workflows.
Estimated time savings, error reduction, and payback timeline.
Duration: 1–2 weeks
Design is where we turn discovery insights into a technical blueprint. We make architectural decisions, plan integrations, and define acceptance criteria—all before writing a single line of code.
System components, data flows, integration points, and technology choices.
Authentication, permissions, data encryption, audit logging.
API usage costs, compute, storage, and ongoing operating expenses.
Clear success metrics: accuracy thresholds, performance targets, error handling.
Technical risks, dependencies, and mitigation strategies.
How we'll validate functionality, edge cases, and error handling.
Duration: 4–16 weeks (depending on complexity)
Build is where we develop the automation or AI system in short, iterative sprints. You'll see working functionality every 1–2 weeks, with continuous opportunities to test, provide feedback, and refine.
We work in short sprints with clear goals and deliverables each cycle.
Code is version-controlled, tested, and deployed to staging environments regularly.
Unit tests, integration tests, and evaluation suites (especially for AI agents).
You see progress weekly. We review together, collect feedback, adjust priorities.
Graceful failures, retries, alerts
Logs, metrics, performance tracking
Secrets management, permissions, audit logs
Code comments, API docs, architecture notes
Duration: 1–2 weeks deployment + optional ongoing support
Operate is about getting the system into production, ensuring your team can maintain it, and (optionally) providing managed support. We don't just hand off code—we ensure successful adoption.
Move from staging to production with zero downtime, monitoring, and rollback plans.
Hands-on training for your team: how it works, how to troubleshoot, how to extend.
Runbooks, troubleshooting guides, architecture docs, API references.
Dashboards, alerts, logging, and performance tracking.
We monitor closely for the first 2–4 weeks, handling any issues that arise.
Code walkthrough, decision rationale, future enhancement guidance.
What you can expect when working with OptimizeLeap
No surprises. We share progress, challenges, and costs openly. You always know where we are and what's next.
This is a partnership. We work closely with your team, incorporate feedback, and ensure you're part of key decisions.
We recommend what works, not what's trendy. Sometimes the answer is "don't build this yet" or "use a simpler tool."
We build systems your team can understand and maintain. No black boxes, no proprietary lock-in.
Security, privacy, and compliance aren't afterthoughts—they're baked into our design process from day one.
We measure success by business outcomes: time saved, errors reduced, costs lowered, revenue protected.
Let's begin with a discovery call. We'll understand your challenge, explore whether automation or AI makes sense, and outline a clear path forward.