Work

Examples of the problems we help teams solve. Real challenges, concrete outcomes.

ReliabilityArchitectureObservability

Healthcare Platform

Appointment Booking at Scale

The Problem

Critical appointment booking system was unreliable under peak load. Missed bookings, frustrated users, lost revenue.

What We Did

  • 1Diagnosed bottlenecks in booking pipeline
  • 2Redesigned queue architecture for peak handling
  • 3Implemented observability and alerting

Outcomes

  • 99.9% booking reliability (up from 94%)
  • Zero missed bookings during peak hours
DeliveryProcessDevOps

B2B SaaS Company

Release Risk Reduction

The Problem

Releases were risky and unpredictable. Team avoided shipping on Fridays. Rollbacks were common.

What We Did

  • 1Audited CI/CD pipeline and testing gaps
  • 2Introduced staged rollouts and feature flags
  • 3Built incident response playbooks

Outcomes

  • Release confidence increased—team ships any day
  • Rollbacks reduced by 80%
ProcessLeadershipProduct

Growth-Stage Startup

Product & Engineering Alignment

The Problem

Product and engineering weren't aligned. Roadmap changed constantly. Engineers felt like task-takers.

What We Did

  • 1Facilitated product-engineering sync process
  • 2Introduced outcome-based roadmap planning
  • 3Coached PMs and engineering leads on collaboration

Outcomes

  • Roadmap stability improved significantly
  • Team velocity increased after initial dip
AISearchElasticsearchML

E-Commerce Platform

AI-Powered Search & Discovery

The Problem

Product search had high zero-results rate and poor relevance. Users couldn't find what they needed.

What We Did

  • 1Implemented hybrid search (Elasticsearch + semantic vectors)
  • 2Built relevance evaluation framework
  • 3Tuned ranking with user behavior signals

Outcomes

  • Zero-results rate reduced by 60%
  • Search-to-purchase conversion up 35%
AITransformationStrategyProcess

Professional Services Firm

AI Era Transformation Sprint

The Problem

Team drowning in tools, no adoption, no measurable impact from AI investments.

What We Did

  • 1Picked 3 workflows to redesign (client proposals, research, reporting)
  • 2Trained team leads on AI-first processes
  • 3Shipped templates + guardrails for quality control

Outcomes

  • Proposal creation time cut in half
  • Research quality improved with better sourcing
  • Team adoption reached 80% within 4 weeks

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