The hard part of AI — done right.
Stryki is an enterprise AI platform company. We train and build models — custom ML and post-trained frontier models — and we build the agents and production AI systems that put them to work — software that doesn't just answer, but plans, uses your tools, and finishes the job — deployed in your cloud, governed by design, and owned by you.
Two things stand between you and AI in production.
The strategy problem
Most AI budget gets spent proving the wrong things. Knowing which use cases actually pay for themselves — and which to leave alone — is a discipline of its own, and it happens before a line of code.
The production problem
A demo is easy. A system your regulators and customers trust, that stays accurate as the world moves and that your team can run without you, is the hard part — and it's where most pilots quietly die.
We own both — end to end.
Strategy at the top, agents at the frontier, and the data, models, governance, and operations that carry a build from a roadmap to a running system you keep.
See the full stack →Watch an agent scope your workflow.
Describe something repetitive your team does. Our agent drafts a real solution architecture on the spot — approach, components, stack, the human checkpoint, and a timeline to a working v1.
Your blueprint appears here — the approach, system components, likely stack, the human checkpoint, and a realistic timeline to a working v1.
We train the models. We build the systems.
Two disciplines, one accountable team — from a custom-trained model to the production system it runs in.
Train Models
We build custom predictive and ML models from your data, and post-train frontier models — SFT, RLHF, DPO, domain adaptation — proving every gain on held-out evals before it ships. You own the model.
Build AI Systems
We build the production systems around those models — retrieval-grounded copilots, document AI, and autonomous agents wired to your tools, governed by design and built to run without you.
Outcomes, measured in production.
Representative engagements — each number links to the full write-up.
Six disciplines. One system.
Strategy at the top, agents at the frontier, and the data, models, and governance that hold it all up. Each links to a full breakdown.
AI Strategy & Roadmap
Find the use cases worth doing, model the ROI, and leave with a sequenced build plan — a portfolio of experiments, not a slideware vision.
Explore → 02Data & ML Engineering
Governed pipelines, feature foundations, and predictive models — the substrate every other layer of the stack stands on.
Explore → 03Generative AI
Retrieval-grounded assistants and copilots wired to your knowledge and systems — answers with citations, not guesses.
Explore → FrontierAgentic AI
Autonomous agents that plan, call your tools, and complete whole workflows — with human gates on the decisions that matter.
Explore → 05Governance & Safety
Evaluation, guardrails, and audit trails built in from day one — AI you can defend to regulators, customers, and your board.
Explore → 06AI Operations
Monitoring, drift detection, and continuous improvement for deployed systems — value that compounds instead of decaying.
Explore →Agents that do the work — safely.
Beyond chat: agents that plan, use your tools, and take action across voice, code, and your workflows — every one grounded in your data and gated by a human where it counts.
Build AI agents
Agents that plan, call your tools, and complete whole workflows — with retries, verifiers, and human gates.
Voice agents
Real-time phone agents that talk like a person, act on your systems mid-call, and hand off cleanly.
Coding agents
Repo-aware agents that edit code, run the tests, and open a pull request for your engineers to approve.
Agent governance
The controls that make agents safe to deploy — permissions, approval gates, trajectory evals, and audit.
Your next hire might not be a person.
For thirty years the pattern was fixed: buy software, then staff people to operate it. That is inverting — teams now describe a job and hire an agent to do it. An agent has a role, tools, boundaries it cannot cross, a manager who reviews its work, and a performance record. It simply happens to be software.
Underwriting Analyst Agent
Pulls the application, bureau file, and financials, checks them against your credit policy, and drafts a recommendation with reason codes attached to each factor.
Every decline, every policy exception, and any file it cannot fully evidence.
Tier 0 · drafts for approval
See it shipped →Representative agent patterns from our engagements — scope, tooling, and autonomy are designed per client.
We build and train the models — not just wire up an API.
Off-the-shelf APIs get you part of the way. For the hardest problems we build custom models and post-train frontier ones on your data, your domain, and your judgment — then prove the gain on held-out evals before anything ships.
Custom predictive models
Risk, forecasting, propensity, and churn models we build from your data and validate with explainability and reason codes — never black boxes.
Fine-tuning & post-training
We adapt frontier models to your domain, voice, and format with supervised fine-tuning and preference optimization — proven on evals, not assumed.
Training data & synthetic generation
The data training needs — curated, labeled, and where privacy or coverage demands it, synthetically generated and validated against real distributions.
Evaluation & benchmarking
Held-out evals and task benchmarks that prove the model you trained actually beats the baseline — factuality, task success, and safety.
Deploy & retrain
Trained models shipped behind an API with monitoring, drift detection, and scheduled or triggered retraining — plus routing to keep cost in check.
Custom copilots & agents
Retrieval-grounded copilots and agentic systems built and tuned to your workflows and tools, evaluated for reliability before they ever act.
The hard problems behind reliable AI.
A demo is easy; a system that's correct, grounded, and safe in production is a research problem. We work the parts that decide whether enterprise AI holds up — evaluation, agent reliability, retrieval quality, and safety — and fold what we learn straight back into what we build.
Task benchmarks, factuality & citation coverage, run in CI.
Verifiers, recovery, and trajectory evaluation.
Hybrid retrieval, rerankers, hallucination control.
Refusal design, jailbreak & bias testing.
Intelligence shaped by your domain.
Deep, current expertise in regulated, high-volume industries — so every roadmap and every system comes wired with real context, not generic prompts.
A partner that ships, and hands you the keys.
Evidence over opinion
Backtests, shadow modes, and A/B splits before belief. We let your data do the arguing.
Whitebox — you own it
Transparent methods and full IP handover. No black boxes, no lock-in to us.
Production over prototypes
Every engagement targets a system your team actually uses in the loop.
Governed by design
Human gates, evaluation, and monitoring from day one — not bolted on after an incident.
Success stories from the stack.
Consumer lending, decided in hours
The save desk that starts with context
What partners tell us.
They came in with an honest read — including the workflow we shouldn't automate yet. That candor is why we trusted them with the one we did.
Ninety days in we had a system in production our risk committee could actually defend — not a slide deck. The audit trail is what sold it internally.
They handed us the code, the prompts, and the eval harness and walked us through running it ourselves. No lock-in, no black box — exactly what was promised.
Representative, composite feedback illustrating typical engagements; not attributed to specific named clients.
Built for the enterprise from day one.
Security, compliance, and governance aren't bolted on at the end — they're how every system is architected. Deployed in your environment, aligned to your controls, and owned by you.
Security & compliance
SOC 2 Type II practices, ISO 27001 and HIPAA/GDPR-aligned controls, encryption in transit and at rest, and independent third-party audits.
Deploys in your environment
Your cloud, your VPC, or on-prem and air-gapped. Models and data run inside your perimeter — nothing has to leave it.
Your data stays yours
Your data grounds the systems and is never used to train foundation models. Full IP handover — code, prompts, models, and pipelines.
Identity & access
SSO and SAML, SCIM provisioning, role-based access, and least-privilege service accounts wired to your identity provider.
Governance & audit
Model-risk controls, evaluation suites, end-to-end audit trails, and human-in-the-loop gates on every consequential decision.
Scale & reliability
Monitoring, drift detection, cost controls, and clear SLAs — production systems that stay accurate and affordable as volume grows.
Controls and certifications shown are representative of an enterprise engagement; specific attestations are established per client and program.
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.