What We Build
From AI concept to working product.
Five services, one through-line: we take you from a problem worth solving to software that solves it. You can engage at any point in that chain.
Find the right starting point for your situation
How the services connect
Most engagements enter at Strategy or Build. Some start at Integration. You don't need all five — but each service is designed to connect cleanly to the next if you need it.
Technologies we build with
AI Product Strategy
Founders and product leads who aren't sure yet whether to build an AI-native feature, automate an existing process, or buy a solution off the shelf.
We run a structured discovery sprint that maps your process landscape, identifies where AI creates real leverage (not just where it sounds plausible), and produces a prioritised use-case shortlist you can act on. The output is a specific, sequenced roadmap — not a slide deck of possibilities.
Most teams skip this step and build the wrong thing. A two-week strategy sprint costs a fraction of a misallocated three-month build, and it tells you whether to proceed at all.
2-week sprint → written output → optional build handoff
Use-case priority map
What you get
- Prioritised use-case shortlist with feasibility and value scoring
- A 90-day sequenced roadmap with implementation dependencies mapped
- Build-vs-buy recommendation with cost model and risk flags
Use-case priority map
Workflow Automation & Copilots
Ops, support, and product teams with repetitive coordination overhead — approvals, routing, data entry, status chasing, manual enrichment — consuming hours every week.
We map the process, identify the automation boundary (what AI handles vs what stays with humans), and build a system that runs reliably in your operational environment. This includes AI decision-support layers that help your team move faster without removing human judgement where it matters.
Automation works best when it's designed around the failure modes, not just the happy path. We build with exception handling, audit trails, and escalation logic from the start — so the system handles edge cases without creating new manual work.
3–6 week build → deployment → optional operations retainer
Automation flow
What you get
- Process map with automation boundary and exception handling defined
- Working automation deployed to your environment with full audit trail
- Runbook and monitoring setup so your team can own it going forward
Automation flow
Web & Mobile App Development
Founders with a validated idea who need a first version in users' hands, and product teams who need a production-grade build they can grow on.
We scope, design, and build — full-stack web, iOS, and Android. We focus the first version on the core workflow that validates your hypothesis, with instrumentation to measure what's working before adding the next layer. No feature creep, no scope inflation.
A six-week MVP isn't a corner-cutting exercise. It's a forcing function on clarity — if you can't describe the three things the first version must do, you're not ready to build. We'll tell you when you are.
Scoping week + 5-week build → production launch
MVP delivery timeline
What you get
- Scoped spec covering core flows, edge cases, and success metrics
- Working product shipped to production with analytics and error monitoring
- Growth-ready codebase with documented architecture for your next hire
MVP delivery timeline
Systems Integration
Teams with AI systems, SaaS tools, CRMs, and data sources that don't communicate — creating data silos, manual reconciliation, and fragile glue code.
We design and build integration layers that connect your stack into one coherent, maintainable system. APIs, webhooks, data pipelines, auth and access controls — built to be observable, resilient to partial failures, and easy to extend when your stack changes.
Most integration failures aren't about the APIs — they're about the assumptions baked into the glue code that nobody documents. We make integration logic explicit, testable, and visible.
1-week design + build sprint → integration testing → deployment
Systems integration layer
What you get
- Integration architecture diagram with data flow and failure modes documented
- Working integration layer deployed with structured logging and alerting
- Auth and access control model with role definitions
Systems integration layer
Monitoring, QA & Iteration
Teams who have shipped an AI system or product and need confidence it's working — and a process to improve it over time without rebuilding from scratch.
We implement observability across your system: accuracy tracking, latency and cost monitoring, user adoption analytics, and failure mode logging. Then we run structured iteration cycles — reviewing what the data shows and making targeted improvements on a cadence that fits your team.
AI systems don't degrade loudly. Accuracy drops a few percentage points, edge cases accumulate, and by the time someone notices, the damage is done. Early monitoring prevents the expensive rebuilds.
Setup sprint (1 week) → ongoing monthly retainer or one-off audit
AI system health
Live94.2%
Accuracy
142ms
Latency
0.3%
Errors
What you get
- Observability setup with dashboards covering accuracy, latency, cost, and adoption
- Failure mode registry with triage and escalation rules
- Iteration backlog prioritised by impact, reviewed on a weekly or bi-weekly cadence
AI system health
Live94.2%
Accuracy
142ms
Latency
0.3%
Errors
Common questions
Things people ask before they reach out.
What's the minimum engagement?
A two-week AI strategy sprint. If you already have a clear use case and want to go straight to build, we scope in a discovery call and move within a week.
Do you work with teams who already have engineers?
Yes. We can work alongside your existing team — embedding into your delivery process — or run a standalone workstream. We're used to both.
What if we're not sure what we need?
Start with a call. We'll ask questions until we understand the problem, then tell you what makes sense — even if that means starting smaller than you expected.
Do you offer ongoing support after launch?
For AI systems, yes — ongoing monitoring and iteration retainers are available. For product builds, we hand off with documentation, architecture notes, and availability for async questions.
Can you work with our existing AI setup?
Usually yes. We're model-agnostic and stack-agnostic. Tell us what you're running and we'll tell you honestly whether we can extend it or whether a cleaner approach is worth considering.
How do you handle confidentiality?
Standard NDA before discovery. We don't use client data to train models or share details across engagements. Happy to sign your template if you have one.
Not sure where to start?
Tell us what you're trying to solve. We'll tell you which service fits — or whether you need all of them.