AI Development
Production LLM systems — RAG pipelines, fine-tuned models and evaluation harnesses that hold up under real traffic.
- RAG & vector search
- Model evaluation
- Inference cost tuning
Ten disciplines, one senior team, one board. We take a product from a first conversation through to something running in production with monitoring on it — and we stay after launch.
Production LLM systems — RAG pipelines, fine-tuned models and evaluation harnesses that hold up under real traffic.
Multi-tenant platforms with billing, roles and analytics built in from day one — not bolted on at month six.
Internal tools and line-of-business systems shaped around how your team actually works.
Fast, accessible, SEO-ready web apps on Next.js and Laravel that score green on Core Web Vitals.
Cross-platform iOS and Android apps with offline-first sync and native-grade motion.
Design systems, prototypes and interfaces engineers can build without guessing at intent.
AWS architecture, containerised deploys and IaC that keeps your bill predictable as you grow.
Replace the spreadsheet-and-email workflow with systems that run themselves and report honestly.
Connect ERPs, CRMs, payment rails and third-party APIs with retries, webhooks and clean contracts.
Autonomous agents with tool access, guardrails and human-in-the-loop review where it matters.
Pick the shape that matches your certainty. Most clients start with one and move to another as the product matures.
A defined deliverable, a fixed price and a written timeline. Best when the requirements are clear enough to lock.
Two to six engineers embedded in your sprints on a monthly retainer. Best for ongoing product work.
Architecture review, AI strategy or a second opinion before you commit. Usually two to four weeks.
A rhythm we've run more than fifty times. You always know what's happening this week and what lands next.
We map the problem, the users and the constraints — then agree on what success actually measures.
Wireframes to a full design system, with clickable prototypes reviewed before a line of code is written.
Two-week sprints against a shared board. Every sprint ends in something you can click, not a slide.
Automated suites, load tests and accessibility audits run in CI on every pull request.
Zero-downtime deploys, monitoring wired up and a rollback plan we've actually rehearsed.
SLA-backed support, monthly performance reviews and a roadmap that keeps moving after go-live.
We pick tools with long support horizons and deep hiring pools — so your system stays maintainable long after we hand it over.
Working with something else? We've shipped on Go, .NET, Flutter, Kubernetes and Snowflake too — ask.
We've spent enough time in each of these to know the regulations, the edge cases and the workflows that actually matter.
HIPAA-aware clinical tooling
Plant-floor visibility
Auditable decision systems
Learning platforms at scale
Listings, CRM and tours
Routing and fleet ops
POS and inventory sync
Composable storefronts
If yours isn't here, ask it directly — we answer within one business day.
An MVP usually lands in 8–12 weeks. Smaller automation or integration work often ships in 3–4. After discovery we give you a scoped timeline with sprint milestones, and you see a working demo every two weeks — so slippage is visible immediately, not at the end.
Book a free 30-minute consultation. We'll pressure-test the idea, sketch an architecture and give you a realistic timeline — whether or not you end up working with us.