
Self-Describing Interfaces
Readable by both humans and AI agents. No manual mapping.
Make everything readable, writable, and ready for AI. Even if you’re just starting to think about your lab's future, UniteLabs helps you lay the foundation today.

Bridging the gap between digital intelligence and physical execution means rethinking the entire infrastructure - from access and integration to data context.





With UniteLabs, devices expose their capabilities in both machine- and human-readable formats. That means AI agents and people can read, understand, and act. No manual mapping required.
Our libraries provide the digital building blocks and real-world context for AI-based workflow generation. We’re the logical link between your lab and AI-powered discovery.
Go from hypothesis to execution faster. UniteLabs gives AI agents low-level control of lab hardware to run experiments, adapt in real time, and continuously optimize protocols.
From interface to infrastructure, every UniteLabs feature was designed to make AI work in the lab. Not just watch from the sidelines.

Readable by both humans and AI agents. No manual mapping.

Directly control devices for faster responses times.
Prebuilt modules for labware and more, ready to use.

Enriched data for smarter interfaces and real insight.

Train AI on how your lab really works. End to end.

Run, monitor, and optimize from anywhere AI lives.
If you have more queries about building AI-driven labs then contact us. We'd love to hear from you.
While the platform is not open source, we provide SDKs, detailed documentation, and APIs to ensure you can build and extend without guesswork.
It’s an interface that explains itself - literally. Devices report their capabilities, limitations, and status in a structured way so AI agents (and humans) can understand and interact without manual setup.
Machine-readable data is structured in a format that computers can instantly interpret - like JSON, YAML, or XML. In our case, it means devices and data speak a language AI can work with out of the box.
We connect your lab to the tools AI needs: Python-based automation, self-describing interfaces, cloud execution, and enriched context. You don’t need to retrofit - AI compatibility is built-in from day one.
Your workflows are written in Python, built on open standards, and owned entirely by you. There's no proprietary runtime, no black box, and no automation that only works inside our ecosystem. Whatever happens, your code stays yours.
That's totally fine. Our platform works just as well for engineers and scientists who want flexible, scalable automation without AI (yet).
We add context: metadata about labware, liquid classes, timestamps, usage history, and more. That means better traceability, smarter automation, and AI that actually knows what’s going on.
Yes. UniteLabs gives you the infrastructure to feed your models real lab data - structured, contextual, and timely - so you can experiment, iterate, and improve with confidence.
Any model you can connect via API. That includes OpenAI, Anthropic, or your own fine-tuned models.
AI agents on UniteLabs operate within defined boundaries — they can only execute actions the platform explicitly exposes, with no freeform hardware access. When something goes wrong mid-run, the platform captures the full execution state at that point: device positions, deck configuration, labware, liquid volumes. Workflows pause, and operators are prompted to verify physical conditions before anything resumes. The platform is designed to escalate to a human rather than guess.
Discover our modular platform, built to connect, scale and simplify every part of your lab.
From low-level pipetting to cross-platform fleet control: do it all, in code.
Capture, clean, and connect every datapoint for smarter decisions.
No pitch. No pressure. Just real conversations about how we can help your lab run better - today and tomorrow.