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SERVICES

Web development and applied AI delivery, focused on outcomes

We build web platforms and AI features with production constraints in mind: reliability, performance, observability, security, and handover. Engagements are scoped and delivered with clear milestones instead of vague staffing.

Common problems we get pulled in to fix

Most engagements start with a few issues that internal teams or generic vendors could not close.

Web apps that are slow, unstable, or painful to change

We stabilize performance, remove recurring incident causes, and reshape the codebase so feature work becomes predictable again.

Integrations that drift out of sync

We design integration flows with retries, idempotency, and monitoring so data stays consistent across systems and failures are visible.

AI experiments that never become product features

We turn prototypes into production features with guardrails, evaluation, observability, and UX designed around trust.

Automations that create more operational mess than value

We implement controlled automation with clear failure handling, auditability where needed, and measurable reduction in manual work.

Internal tooling held together by spreadsheets and manual steps

We build internal tools that match real workflows, reduce errors, and make operations faster without creating a new monster to maintain.

Unclear scope and endless iteration loops

We bring scope discipline and clear “done” definitions so the work completes and the value lands.

Core areas of work

These are the engagement types we run most often, either standalone or bundled into one delivery roadmap.

Web platforms and product builds

Customer-facing apps, portals, dashboards, internal tools, and full-stack systems designed for reliability and change.

  • Clear architecture and clean delivery boundaries
  • Performance, monitoring, and security considerations included
  • Testing strategy aligned with risk and velocity

Applied AI and LLM-enabled workflows

RAG systems, assistants, document processing, extraction, and workflow features that integrate into the product.

  • Guardrails and evaluation built into delivery
  • UX designed for trust and control
  • Observability for prompt, retrieval, and outputs

Integrations and orchestration

APIs, event flows, background jobs, and cross-system automation with real error handling and visibility.

  • Retries and idempotency where it matters
  • Monitoring and alerting to avoid silent failures
  • Auditability across systems when required

Stabilization and replatforming

Fix fundamentals without stopping feature delivery. Reduce risk, improve performance, and make the codebase understandable again.

  • Identify hotspots and recurring failure points
  • Incremental refactors with measurable improvements
  • Documentation and handover that survives turnover

Delivery model

Work is structured to reduce risk for both sides. Scope, progress, and decisions stay visible instead of hiding behind vague “capacity”.

Scoped, outcome-based projects

Engagements are organized around outcomes, milestones, and decision points, so both sides know what will be delivered and when.

Single accountable lead

Each engagement has one accountable delivery lead, reducing hand-offs and giving your team a clear technical point of contact.

Handover and support

Every delivery includes documentation and structured handover. Ongoing support is defined explicitly instead of being implied.

Align delivery with your roadmap

If you already know what needs to be built, we can scope it fast. If not, we can start with discovery and a short technical plan.