Sparzan designs and builds custom AI software — autonomous agents, AI-native UI/UX, and production systems that think, act, and scale.
Left: how AI usually ships. Right: how Sparzan ships it. Same team, wildly different curves.
We pair deep AI engineering with product design to deliver software that does real work — not demos.
Autonomous agents that plan, use tools, and complete multi-step workflows reliably in production.
Custom applications with AI at the core — built end to end, from data layer to polished interface.
Interfaces designed around intelligence — adaptive, conversational, and beautiful by default.
We analyze your data, decode your workflows, and ship AI systems that earn their keep in production. Consulting alone isn't enough — we build what we recommend.
Driving Force Behind SparzanWe build agents that reason over your tools and data, take actions, and stay within guardrails you control. Observable, testable, and production-ready from the first commit.
Slack, Linear, your DB — the agent adapts to your stack, not the other way around.
State machines gate high-stakes actions. LLMs handle the reasoning; you decide the branches.
Every run is queryable. Every deploy runs the eval suite. No surprises after handoff.
Sparzan is a small team of engineers and designers who ship AI products that hold up in production. No outsourcing, no junior bait-and-switch. Every engagement is led by someone who's built and shipped agentic systems before.
Every project is led by an engineer who has shipped production AI systems, not someone learning on your budget.
AI without product judgment ships demos. We build for the user behaviour the system will actually live inside.
We tell you what is and isn't possible inside your timeline and budget. No upsells, no theatre, no scope creep dressed as discovery.
Four phases. Every engagement, no matter the scope.
Kickoff sync on your tech stack, your team's rituals, and the immediate wins. We ship an eval scaffold before we write any prompts.
Prioritize the workflows where an agent compounds. Everything is measured against a target eval score and a target cost-per-call.
Agents, tools, evals, guardrails. Shipped to a staging environment behind a feature flag with full tracing from the first commit.
Iterate against real traffic. Tune cost, latency, and eval pass rate. Hand off with runbooks, on-call docs, and a maintenance contract if you want one.
Anonymized for now while NDAs lift. Real outcomes, real production systems.
Tier-1 ticket resolution agent with policy-aware drafting, MCP-connected to the CRM, and a full eval suite gating every deploy.
Multi-source research and synthesis with cited, verifiable output and a reviewer-in-the-loop UI for analyst sign-off.
Conversational interface that turns plain-English prompts into editable production UI, wired into a token-aware codegen layer.
Six things every Sparzan engagement gets from day one.
2–4 week pilots to a production-shaped prototype, not a slideshow of "possible integrations."
Every deploy passes a shipped eval suite. No silent regressions, no vibes-based QA on production traffic.
Code lives in your repo, runs on your infra, ships through your pipeline. No black-box vendor lock-in.
Claude, GPT, open-weight — we architect for swaps, so tomorrow's better model is a one-line change.
Traces, costs, drift, and success rates surfaced in dashboards your team already uses — not a new vendor UI.
Every engagement is led by someone who's shipped production AI. No juniors learning on your budget.
Fixed-scope pilots, monthly retainers, or embedded senior engineering. Written scope + pricing on the first call — no black-box billing.
Map the workflow, build an eval scaffold, and ship a functional prototype behind a feature flag.
End-to-end build: agent, tools, evals, observability. Deployed behind a flag with full tracing from day one.
Senior AI engineering embedded with your team. Ships against your roadmap, hands off nothing.
All engagements ship code in your repo, run on your infra. No vendor lock-in, no royalty on the agent output.
They were the only team that walked into our review with hard eval numbers, not a slideshow. That alone got them the contract.
Senior from day one. Our previous vendor took 6 weeks to get to a demo; Sparzan had a production agent behind feature flags in three.
They said no to two of our ideas because the eval cost-per-call didn't pencil out. That's the kind of consultant we wanted.
Field notes on building AI products that hold up after launch.
The gap between a hot demo and a system you can page on at 3am, and the five eval categories that close it.
Writing tests for non-deterministic systems. How we treat eval suites as the actual contract, not the model weights.
Multi-agent orchestration is a tax most products don't need yet. When one well-tooled agent beats a swarm.
The five we hear on almost every discovery call.
Tell us what you're working on. We reply within one business day — no qualification form, no black-box pitch deck.