If it runs on code,
we build it.

Frontend

• React, Next.js, and TypeScript, server-rendered or single-page

  We build for the modern web: server components, streaming, and edge rendering where they earn their keep, with a design system underneath so the hundredth screen is as consistent as the first.

• Design systems and component libraries
• Progressive web apps with offline support

Backend & data

• REST and GraphQL APIs, services, and authentication

  The server side is engineered as carefully as the screen: clear domain boundaries, sound data modeling, and APIs stable enough for other teams to depend on.

• Relational and NoSQL data modeling
• Real-time features over websockets and event streams

Native & cross-platform

• Native iOS in Swift and Android in Kotlin
• Cross-platform with React Native and Flutter

  When one codebase makes sense, we ship cross-platform without the usual compromises: native modules where performance demands them, and a UI that feels native on each OS.

Lifecycle

• Offline-first sync and local storage
• Push notifications and deep linking
• App Store and Google Play release management

Interfaces

• REST, GraphQL, and gRPC APIs

  We design APIs as products: versioned, documented, and stable, so the teams and partners who build on them can move fast without fear of a breaking change.

• Authentication, authorization, and rate limiting
• Webhooks and event-driven integration

Services

• Microservices and well-structured modular monoliths
• Background jobs, queues, and schedulers
• Caching, search, and high-throughput data paths

Design to code

• Design systems, tokens, and component libraries

  One source of truth for how the product looks and behaves, so design and engineering stop drifting apart and every team ships consistent work.

• Interactive prototypes that become production code
• Motion and micro-interaction

Quality

• Accessibility to WCAG standards
• Performance budgets and Core Web Vitals
• Cross-device and cross-browser fidelity

Pipelines

• CI/CD with automated testing and deployment gating

  Every commit is built, tested, and deployable. Routine, boring releases are the single best predictor of a healthy engineering org, and that is what we build toward.

• Infrastructure as code with Terraform
• Containerization with Docker and Kubernetes

Clouds

• AWS, Azure, and Google Cloud
• Cost optimization and FinOps
• Multi-region and disaster recovery

Developer experience

• Internal developer platforms and golden paths

  Self-service templates, environments, and paved roads so a new service goes from idea to production in hours, with security and observability already wired in.

• Self-service environments and scaffolding
• Observability: logging, metrics, and tracing

Operations

• Service catalogs and paved roads
• Secrets, configuration, and policy as code

Reliability

• SLOs, error budgets, and on-call practices

  We make reliability a number, agree on it, and engineer to it, so the trade-off between shipping features and keeping the lights on is explicit instead of accidental.

• Monitoring, alerting, and incident response
• Autoscaling and capacity planning

Resilience

• Chaos testing and failure injection
• Blameless postmortems and reliability reviews

Secure SDLC

• Threat modeling and secure design reviews

  We find the weaknesses on a whiteboard, before they are written into code, then keep the pipeline honest with automated scanning at every stage.

• Static and dynamic analysis in the pipeline
• Dependency and supply-chain scanning

Assurance

• Penetration-test remediation
• SOC 2, HIPAA, and GDPR readiness
• Identity, secrets management, and encryption

Movement

• Batch and streaming ETL and ELT

  Whether the requirement is nightly batch or sub-second streaming, we move data reliably, with the lineage and quality checks that let people trust what they see.

• Data warehouses and lakehouses
• Change-data-capture and real-time sync

Trust

• Data modeling and a semantic layer
• Quality, lineage, and governance

Applied AI

• LLM applications, retrieval-augmented generation, and agents

  We build AI that ships: generation grounded in your own data, with evaluation, guardrails, and cost controls, not a demo that falls over the moment a real user touches it.

• Predictive models and recommendation systems
• Computer vision and document intelligence

MLOps

• Training, evaluation, and deployment pipelines
• Monitoring for drift and performance

Insight

• Dashboards and embedded analytics

  Analytics where the work happens: live metrics embedded in your product and your operators' tools, not a separate portal nobody opens.

• Metrics and semantic layers
• Self-serve exploration for non-technical teams

Foundations

• Event tracking and product analytics
• Experimentation and A/B frameworks

Find

• Full-text and vector search

  We combine classic keyword search with semantic, vector-based retrieval, so users find what they meant, not just what they typed.

• Ranking, relevance, and tuning

Personalize

• Recommendation and personalization engines
• Hybrid and semantic search

Approach

• Strangler-fig migration, with no big-bang risk

  We stand the new system up beside the old, move functionality piece by piece behind a stable facade, and retire the legacy code only once its replacement is proven in production.

• Re-platforming and re-architecture
• Automated test harnesses to protect existing behavior

Outcomes

• Lower maintenance cost and operational risk
• A codebase your team can actually hire for

Path

• Assessment and migration strategy across the six Rs

  Rehost, replatform, refactor, repurchase, retire, or retain: we decide each workload on evidence, not dogma, and sequence the move to de-risk the business.

• Lift-and-shift through full re-architecture
• Data migration with validation and rollback

Value

• Cost optimization once you are there
• Security and compliance baked into the target

Connect

• API and event-based integration

  We replace brittle nightly file transfers with real-time, event-driven integration that is observable, idempotent, and safe to retry, so a hiccup in one system never corrupts another.

• iPaaS and enterprise service buses
• ERP, CRM, and third-party connectors

Keep in sync

• Master-data and real-time synchronization
• Idempotency, retries, and reconciliation

Automation

• Unit, integration, and end-to-end suites

  A test pyramid that actually holds: fast unit tests, focused integration tests, and end-to-end coverage of the journeys that matter, all gating the pipeline.

• CI gating so nothing ships untested
• Visual and contract testing

Strategy

• Test strategy and coverage planning
• Test data and environment management

Speed

• Load testing, profiling, and optimization

  We find the real bottleneck instead of guessing: load tests that model production, profilers that point at the hot path, and fixes that move the metric you care about.

• Core Web Vitals and frontend performance
• Database and query tuning

Scale

• Capacity and throughput planning
• Caching and concurrency strategy

Review

• Architecture and code audits

  A clear-eyed assessment of an existing system: what is solid, what is risk, and what to do about it, in language both engineers and executives can act on.

• Technical due diligence for investors and acquirers
• Security and reliability assessments

Direction

• Architecture decision records and roadmaps
• Hands-on mentoring for your team