AI product studio · Est. 2026

Building AI-native products for the next generation of work.

2labs builds software that turns complex workflows into intelligent, automated experiences — combining frontier AI, agentic workflows and product engineering.

We believe the next decade of software won't be measured in features shipped, but in work completed. Our job is to build the products that do that work.

Explore what we're building →Contact

What we're building

Relay · Private beta

The AI-native way to run knowledge-intensive workflows.

Relay helps operations teams go from hours of manual document review to structured, actionable outcomes with an agentic AI workflow.

It ingests documents and data from the tools you already use, reasons over the full context with Claude, and takes action across your systems — escalating to a human only when judgment is actually needed.

Built with Claude.

Try it →

// relay run #2041

→ ingest 38 documents

→ extract entities ✓

→ reason over 212k tokens ✓

→ call tools: crm.update, notify.team ✓

result:

{ status: "resolved", actions: 4, review: false }

Built with Claude

Claude is part of the intelligence layer powering our products.

User
  ↓
2labs Product
  ↓
AI Orchestration
  ├── Claude
  ├── Tools / APIs
  ├── MCP
  └── Internal Knowledge
  ↓
Action / Output

We use Claude for reasoning-intensive workflows, long-context tasks, structured outputs, tool use and agentic execution.

Claude's long context window lets our agents hold an entire case file in memory at once; its tool use and structured outputs let them act on the world reliably, not just talk about it.

Long-context reasoning
Agentic workflows
Structured outputs
Tool use
Code generation
Reliable handling of complex instructions

Claude API · Claude Code · MCP

Why 2labs

Six principles we build by.

Product-first

We build products, not AI demos. Every capability we ship has to survive contact with real users doing real work — not just look impressive in a screenshot.

AI-native

AI is part of the core workflow — not an add-on feature bolted onto a traditional product. We design every screen, API and data model assuming an agent is doing most of the work.

Fast iteration

We use AI throughout development to move from idea to production quickly. Small team, tight loops, weekly releases — the same speed we want our products to give our users.

Boring reliability

Agentic systems fail in unglamorous ways. We invest heavily in evaluation, guardrails and observability so the product is trustworthy on a bad day, not just a good one.

Human checkpoint

Automation should escalate, not hide. When confidence is low or stakes are high, the product asks a human — with full context, not a vague alert.

Own the outcome

We don't sell tokens or seats. We measure ourselves on the outcome the customer cares about: cases resolved, hours returned, errors avoided.

How we work

From messy workflow to shipped product.

Listen

We embed with operations teams and watch how the work actually happens — the spreadsheets, the inboxes, the copy-paste between systems that never makes it into a process document.

Prototype in weeks

We build a working agent against real (anonymized) data within the first few weeks. A rough product on real workflows beats a polished deck every time.

Measure relentlessly

Every agent action is logged, sampled and reviewed. We track accuracy, escalation rate and time saved — and we share those numbers with our design partners.

Harden and ship

Only when the numbers hold do we generalize: permissions, audit trails, SSO, retention policies — the unglamorous work that makes AI safe to deploy.

FAQ

Questions we hear a lot.

Is 2labs a services company or a product company?

A product company. We work closely with design partners, but everything we learn goes into shared product capabilities — not one-off custom builds.

What does "AI-native" actually mean?

It means the product is designed around what AI agents can do, rather than adding a chatbot to a traditional workflow. The agent is the primary worker; the human is the reviewer and decision-maker.

Do you train models on customer data?

No. We use frontier models via API with strict data-handling terms, and customer data is never used for training.

When can I try the product?

Relay is in private beta with design partners now, with a broader launch planned for Q4 2026. Email us to join the waitlist.

Status

Private beta — launching Q4 2026.

Currently testing with early users and design partners. We're onboarding a small number of teams each month so we can stay close to every workflow.

Join the waitlist →

Our mission

Software shouldn't just help people work faster. It should do more of the work itself.

For thirty years, software gave humans better tools. The next thirty will give humans better teammates. We're building for that world.

Meet the team →hello@2labs.tech