We build
the AI products
teams actually use.
Founder-led. Operator-built. Two products live, more in stealth. Each one stands alone — and each one makes the next one faster to ship.
We build
and own products
Praxiom and Polaris are ours, end-to-end — research, design, code, growth. Meterlane is next. Every product can stand alone, and every product reuses the primitives we ship in the open.
See the PortfolioWe co-build
with operators
A handful of engagements per year for operating teams that need an AI-native product shipped, not consulted on. Bounded scope. Real artifacts. Code and IP transfer.
The next great software companies will be built by studios, not solo founders.
Code is a commodity. Taste, distribution, and shared infrastructure are not. Einstein Labs exists to compound all three across a portfolio.
We don't consult. We don't take retainers. We build AI-native products end-to-end — research, design, engineering, growth — and we reuse the primitives across every bet. Two products are live today. More are coming. Each one makes the next one faster to ship.
We are not
- An AI agency
- A holding company
- An accelerator or incubator
- A venture fund
- A single-product company
We are
- Founder-led and operator-built
- End-to-end product owners
- Concentrated — a few bets, deep
- Open source where it compounds
- Funded by what we ship
Method, not magic.
One bet at a time, taken to live.
We don't spread thin. Each product is built end-to-end — research, design, engineering, growth — until it stands on its own in the market.
Founder-led from day zero.
No incubator hand-off. No recruited CEOs from a Rolodex. The people who design the product are the people who ship it, run it, and live with it.
Shared infrastructure compounds.
The harness, the SSE protocol, the eval suite, the agent runtime — built once, reused across every product. Each new bet ships faster than the last.
Open source where it compounds.
Primitives go MIT. Products stay commercial. We give away the substrate and earn the layer above it. ANT, agent-stream, PMEval-1 are the proof.
Artifacts you own, not access you rent.
Customers get the code, the data, the deployment in their own accounts. If the studio disappears, the products keep running. That's the bar we hold ourselves to.
Two products live.
More in stealth.
Each company stands alone. Each one ships on shared infrastructure and contributes back to it. Open source where it compounds.
Praxiom AI.
Research intelligence for product managers.
Atlas, the agent that runs the full PM research-to-output pipeline. Research → Insights → Recommendations → Documents — backed by a multi-agent harness, quality scoring at every stage, and overnight research cycles.
Pre-flight contract negotiation, in-flight stream monitoring, post-flight verification with contrastive scoring. The harness is domain-agnostic and powers every product the studio ships.
- Atlas agent · 5 personas · 3 reasoning modes
- Pre / in / post-flight harness with healing loop
- 10 official PM skills · entropy detection
- Workspace memory · overnight research cycles
Polaris AI.
Spec-driven AI software development.
Describe what you want; Polaris drafts a structured spec, then an autonomous agent loop builds a deployable Next.js + Supabase app inside an E2B cloud sandbox. Verifies its own output. Deploys to your own Vercel and Supabase. Pushes to your own GitHub.
Not a chatbot that writes code. Not a no-code builder. A spec-driven AI development system where the spec is the contract, the agent executes against it, and you own the artifact outright.
- Durable, machine-readable spec — not a chat transcript
- Multi-iteration agent loop · 17 tools · 4 layers of recovery
- tsc + ESLint + build verification before "done"
- Deploys to your Vercel · your Supabase · your GitHub
One product in build, three open source primitives extracted from production.
Meterlane.
Billing infrastructure for AI-native products.
The metering and billing primitive that powers Praxiom and Polaris. Credit-based or seat-based, with hard cost ceilings enforced at the infra layer — not just warnings. The third bet of the studio.
Next bet.
In stealth.
We pick one new bet per year. The next one is already in research. If you want to hear about it before it ships, get in touch.
The primitives we extracted from production. Free, MIT, and used in our own products.
ANT.
Agent-Native Terminal.
CLI for running AI agent definitions. Approval-gated commands, deterministic runs, local-first storage. The agent stays transparent: command, cwd, risk shown before execution.
agent-stream.
SSE protocol for AI agents.
token · thinking · tool_use · tool_result · turn · progress · done. Python emitter + React hook. Extracted from production after 36 agent tools across thousands of runs.
PMEval-1.
PM agent benchmark.
336 tasks · 14 categories · 3 difficulty levels. Tests whether an AI agent can do real product management work — not toy problems. Hallucination-guarded scoring across 5 dimensions.
For PMs
and AI-native builders.
Praxiom for product managers running real research programs. Polaris for founders and engineers shipping AI-native software end-to-end. Both live, both production, both used by real teams today.
See the PortfolioFor operators
who need to ship.
A handful of studio engagements per year for operating teams that need an AI-native product shipped — not a deck, not a prototype. Bounded scope. Real artifacts. Code and IP transfer back to you.
Pitch an engagementFor LPs
and strategic partners.
One studio. Multiple bets. Shared infrastructure that compounds across every product we ship. Concentrated, founder-led, and funded by what we ship. If that's the kind of bet you make, talk to us.
Get in touch