[ BUILD AI SYSTEMS · 06 DISCIPLINES ]
Build AI systems, end to end.
Most AI programs fail between the layers — strategy that ignores the data, models without governance, agents without operations. We take responsibility for the whole stack, so nothing falls in the gaps.
010203040506
AI Strategy & Roadmap
Most AI budgets get spent proving the wrong things.
Data & ML Engineering
The substrate every other layer stands on.
Generative AI
Retrieval-grounded assistants, copilots, and document AI wired to your knowledge and live systems.
Agentic AI FRONTIER
Our frontier practice.
Governance & Safety
Evaluation, guardrails, audit trails, and human-in-the-loop design built in from the architecture stage — so what you deploy is defensible to regulators, customers, and your own risk committee.
AI Operations
Once systems are live, we keep them earning.
Method
Hypothesis to production in five moves.
A sequence, not a slide deck. Each step ends in something real — a measurable claim, an architecture, a running system.
Engagements
Start small, then scale.
Fixed-scope where we can, so you always know what you are buying.
Discovery sprint
Map & plan
~2 weeks · fixed fee
- One workflow mapped end to end
- ROI and feasibility quantified
- Architecture + build plan
Most common
Fixed-scope build
Ship a system
4–8 weeks · fixed per scope
- One production system, live
- Proven on your data first
- Integrated into your stack
- You own the code and models
Embedded AI team
Scale with us
Monthly · retainer
- A Stryki pod alongside your team
- Multiple systems in parallel
- Ongoing governance & AI Ops
FAQ
Common questions.
Are you an agents-only shop?
No — agentic AI is our frontier practice, but we design and build across the whole stack: strategy, data and ML, generative AI, governance, and operations. Many engagements never involve an agent; many others only work because the layers underneath were built right.
Do you work fixed-fee or hourly?
Mostly fixed-scope. We define a clear deliverable and price it, so you know the cost up front. Embedded teams run on a monthly retainer instead.
Who owns the code and models?
You do. Everything we build — code, prompts, fine-tuned models, pipelines — is yours to keep and run. That is the whitebox promise.
Do you train foundation models on our data?
No. Your data stays yours and is never used to train foundation models. We build to your data-handling and compliance requirements.
Which models do you use?
Whatever fits the job and budget — we are model-agnostic and route across Claude, GPT, and open models rather than locking you to one vendor.
How fast can we start?
A discovery sprint can usually kick off within one to two weeks. First measurable value on a build typically lands inside 30 days.
Get started
Bring us a hypothesis. Leave with a system.
Tell us what's eating your team's time. We'll give you an honest read on whether AI is the right tool — and if it is, a scoped v1 with a timeline and cost.