Ship AI that actually works in production.
From a one-day strategy workshop to a fully AI-native product — chatbots, RAG, agents, copilots. AI consultants based in Vancouver, BC, working with teams across Canada and globally. Model-agnostic, eval-driven, built to survive the next model release.
What good AI looks like in production
The six things every Zyra AI engagement leaves you with — non-negotiable.
Model-agnostic by design
Swap GPT for Claude for Gemini in an afternoon. Your business logic doesn't get held hostage to one vendor's roadmap.
Eval-driven, not vibes-driven
Every shipped feature has an eval suite. We measure regression on real data — not screenshots of a demo working once.
Latency you can budget for
p50 and p95 targets per feature, streaming where it helps, caching where it matters. AI that feels instant.
Cost you can forecast
Token budgets, model routing, cache hits — instrumented from day one. You'll know what each conversation costs.
Guardrails + observability
Prompt injection defenses, output validators, structured logging. Production AI you can debug at 2am.
You own the stack
Code, prompts, evals, infra accounts. We hand over keys at launch — no proprietary platform between you and your AI.
Every shape AI takes — under one team
From a chatbot you can demo on Monday to an AI-native platform that's the whole company. Eight things we ship.
AI-native apps
Products where AI is the product — built around models, evals, and feedback loops from day one.
Chatbots & assistants
Customer support, internal Q&A, sales copilots. Streaming, tools, and memory done right.
RAG systems
Retrieval over your docs, knowledge base, or proprietary data — with citations and freshness.
Autonomous agents
Tool-using agents that book meetings, file tickets, or run multi-step workflows safely.
Internal copilots
Domain-tuned assistants for your sales, ops, engineering, or analyst teams.
Workflow automations
AI in the loop — classification, extraction, summarization at production scale.
Document AI
Contract review, invoice extraction, KYC checks — structured outputs from unstructured input.
Voice agents
Real-time voice assistants for phone calls, dictation, or live transcription.
Demos are easy. Production is the job.
The three things that separate a working demo from an AI feature your CFO trusts.
Evals & guardrails
Every prompt has a test suite. Every regression caught before customers see it.
Cost + latency telemetry
Per-route token spend, p50/p95 latency, cache hits — instrumented from request one.
Model + prompt registry
Versioned prompts, A/B model routing, instant rollback. Ship a new model without holding your breath.
Hire the AI lead you don't have
Three engagements — pick the depth that fits where you are.
Workshop
One day with your leadership to map AI's role in your business — and what to ship first.
- Pre-workshop async intake call
- Full-day on-site or remote workshop
- AI opportunity map (high-leverage bets)
- 12-week roadmap with cost/risk per bet
- Written brief delivered within 5 days
Best for SMB and exec teams figuring out where to start with AI.
Advisory
A fractional AI lead embedded with your team — weekly calls, async review, technical depth.
- Weekly 60-min strategy call
- Async architecture + prompt review
- Vendor + model selection guidance
- Eval design + observability setup
- Hiring + scope reviews for AI work
Best for funded startups and mid-market teams building AI without a full-time AI lead.
Embedded
Zyra engineers join your team for a quarter — strategy, building, and knowledge transfer.
- 1-2 senior AI engineers embedded
- Daily standup + sprint participation
- Hands-on prompt + agent engineering
- Eval suite + on-call playbook
- Documented handoff at close
Best for orgs scaling AI features fast and building in-house capability behind it.
All prices in USD. Workshops cap at one company per week — book early. Looking for a build, not advice? Jump to AI-native build pricing.
Or have us build it
One-time engagements with full source-code handoff. Production-grade AI, owned by you.
MVP
A working AI feature — chatbot, internal copilot, RAG over your docs — production-ready in weeks.
- One AI feature, end-to-end
- Auth + Postgres + vector store
- Streaming UI + prompt registry
- Baseline eval suite (5-20 cases)
- 30-day post-launch warranty
- Full source-code handoff
Best for proving an AI feature works on real data with a real budget.
Product
An AI-native product: agents, tool-use, multi-model routing, evals, observability — the whole stack.
- Everything in MVP
- Multi-step agents + tool use
- Model router (cost/latency aware)
- 100+ case eval suite + CI
- Observability + cost dashboards
- Stripe billing + 2 integrations
- 90-day post-launch support
Best for SaaS launches where AI is the core feature — not a sidebar.
Platform
Multi-tenant AI platform with SSO, audit logs, customer-specific tuning, and SDKs.
- Multi-tenant model routing
- Per-tenant prompts + evals
- SSO (SAML, OIDC) + audit logs
- Public SDKs (TS, Python)
- Fine-tuning pipeline (optional)
- 6 months support + team training
Best for AI companies selling AI as a platform to enterprise customers.
All prices in USD. Payment 50% to start, 50% at launch. Optional $2,000/mo maintenance retainer available after handoff. Custom scope beyond Platform quoted on a call.
How we go from "AI could help" to shipped
Four phases. About six weeks for a first feature in production.
Audit
We map your workflows, data, and existing AI bets. Output: a brief on what's actually worth automating with AI — and what isn't.
Strategy
Pick the highest-leverage bet. Define the eval set, the model shortlist, the latency budget, and the cost ceiling. Write the spec.
Prototype
Working prototype on real data, evaluated against the eval set. Iterate prompts, models, retrieval — measure every change.
Production
Guardrails, observability, cost telemetry, runbook. We hand off a feature your CFO trusts and your on-call doesn't dread.
DIY ChatGPT integration vs. a real AI build
A working demo and a production feature are different planets. Here's where most teams find that out the hard way.
A weekend ChatGPT integration is great for proving an idea. Shipping to paying customers is a different sport.
Every major model, every modern tool
We pick the right stack per problem — not the one we're being paid to recommend.
Plus pgvector / Pinecone for retrieval, LangChain / Vercel AI SDK for agents, OpenTelemetry for tracing. The right tool for the problem.
Questions, answered
The things teams ask before letting AI near their production stack.
Stop guessing where AI fits. Find out in a day.
Book a 30-minute call. We'll talk through your current AI bets, what's working, what isn't — and whether a Workshop, Advisory, or Build is the right move.
Book a strategy call