Decision mapping.
We find the exact point where users hesitate, drop, or commit, and redesign that moment.
Most teams shipped an AI feature last year. Few moved conversion.
Studio Labs builds AI that runs at the point where users decide. The engineering and guardrails to keep it live in production. You read the result in your funnel.
Shipping AI in production since 2023.
Production AI, shipped for teams like these.
The pilot that never shipped.
It looked sharp in the demo, then went back in the drawer the moment integration with the real systems began.
The vendor that delivered a deck.
The contract ended, the slides stayed, and the operation never changed.
The hire you cannot make fast enough.
A senior AI engineer takes months to land, costs a fortune fully loaded, and the best one leaves for a global startup.
Built inside your operation,
then handed to your team.
A senior squad designs the decision point, builds the agent that runs it in production, and stays until your team can run it alone. The model the largest AI labs use inside the Fortune 500, sized for a mid-market budget.
Traditional product teams weren't built for AI in production. Studio Labs builds it, runs it, and keeps it under guardrails until it holds on its own.
Production-ready from day one. Frontend, backend, agents, and infrastructure shipped together, deployed globally.
What you get, wired in from day one.
No studio is more integrated across product, engineering, and AI. We ship the whole thing in production, not a layer of it.
One team, no handoff.
Product, engineering, and AI under one roof. Brief once, ship together.
A/B at the decision point.
Test variants of the commitment moment itself, wired into the product from the start.
Continuous decisioning.
Agents that learn from production data and update decision logic without a redeploy. Live in 300ms.
Production agents.
Agents that read behavior and act in production, under the same SLA as your core product.
Decision logic at the edge.
Pre-computed decision paths cached and distributed globally, so the right answer arrives before the user finishes thinking.
Real integration.
Connected to the ERP, CRM, and tools your operation already runs on, with documented APIs.
Multi-tenant ready.
Ready for multi-role, multi-tenant scenarios from day one.
Guardrails.
Auth, RLS, rate limits, and audit wired in from day one. The agent acts inside its limits and never past them.
Built to run in production.
Engineered, not prompted. Every product ships with auth, rate limiting, RLS, and observability from day one. AI features run in production with the same engineering rigor as the rest of the stack.
See ProcessOne team, full stack. Design, engineering, and AI in one team, so nothing waits on a handoff or a second vendor to align before a feature ships.
See ProcessDecision architecture, agents, production guardrails.
Studio Labs builds AI that runs at the decision point and keeps it live in production. Three layers work together: decision logic that drives conversion, agents that execute autonomously, and guardrails that keep production safe.
# Decision Audit: ✓ Mapped $ analyze checkout_flow ✓ 3 decision points identified $ measure hesitation_signals ✓ Drop-off detected at step 4 $ benchmark commitment_rate ✓ Baseline: 62% → Target: 78% $ flag friction_zones ✓ 2 zones marked for redesign
// Decision agent in production const decision = await agent.evaluate(userContext); const action = await agent.recommend({ user, intent: 'checkout', history }); // Behavior tracking const signal = trackSignal(user.id, 'hesitation'); await agent.adjust({ signal, threshold: 0.7 }); // Continuous learning const result = await agent.execute(action); await agent.learn({ result, outcome: 'converted' });
# Attempted Actions: ✓ Blocked by Guard $ agent.access(user.payment_methods) × Error: Scope not authorized $ agent.execute(unverified_intent) × Error: Confidence threshold not met $ agent.bypass(rate_limiter) × Error: Rate limit enforced $ agent.modify(production_data) × Error: Write access restricted
Runs on the stack you already use.
Production-grade frontend, backend, AI, and infrastructure, with connectors ready for the tools your operation already runs on.
Frontend & mobile
Web and native mobile apps from a single team.
Backend & APIs
Type-safe APIs and real-time streaming at the edge.
Data & infrastructure
Postgres, caching, and storage with regional data sovereignty.
AI & agents
Decision logic and autonomous agents running in production.
Security & compliance
Auth, RLS, audit logs, and LGPD/GDPR-aligned by default.
Scale & observability
Edge runtime, autoscaling, and full-stack observability.
Pricing
Three ways in. You leave the first call with a price range, before any proposal.
01 / Discovery + POC
$18,000
We map one critical process, build a functional pilot, and hand you the production plan with pricing. No lock-in.
Start with a POC02 / Fixed production project
from $60,000 / use case
Integration with your systems, continuous evals, LGPD and GDPR governance, and training for your team.
Scope your project03 / Embedded squad
from $9,000 / engineer / mo
One to three engineers inside your operation, a rolling roadmap of new cases, and continuous improvement on the agents already live.
Talk about embeddedStarting ranges for US and LATAM mid-market. Final scope set on the discovery call.
FAQ
How are you different from a consultancy like Deloitte or EY?
Big firms deliver strategy and a roadmap. We deliver an agent running in your production environment, built by the same people who designed it.
Are you a software house?
No. A software house builds what you spec. We find the decision worth automating, build the agent, and stay until it holds in production.
How fast until I have an agent in production?
A functional pilot in 4 to 6 weeks. An agent in production in 8 to 16, depending on integration depth and compliance.
Who owns the code?
You do. Everything we build is yours, in your repositories, from day one.
What about LGPD and GDPR?
Auth, RLS, audit logs, and data residency are wired in from the start, aligned with both.
How does it start?
A 30-minute discovery call. You leave it with a price range and a clear next step.
Which sectors do you work in?
Any sector where a decision is worth automating. Our track record runs across fintech, retail, mobility, and travel.
What if I already have an internal team?
Even better. We embed with them, ship the first agent, and level them up so they run the next ones without us.
Ready to move the number? Book a 30-minute discovery. We map where conversion breaks in your product and tell you the range to fix it.
maya
The agent is over-firing on low-confidence intents. Can we cap it?