The lab that schedules itself.
FluenticOS connects your instruments, your protocols, and your team into one live, audit-ready system. Experiments plan, run, trace, and report themselves, end to end.
Built for hospital, academic, translational, and clinical research labs.
Right now, your schedule lives in five different places.
Every research lab runs on a patchwork: a protocol in someone's head, a spreadsheet everyone half-trusts, and a different piece of software for every instrument. None of it talks to the others, so a scientist has to, and none of it produces an audit trail on its own.
- A shared spreadsheet everyone half-trusts
- A whiteboard for what's running where
- Separate, disconnected software per instrument
- Someone walking the bench just to check on a run
- A scramble to reconstruct who did what before an audit
FluenticOS replaces the patchwork with one system that watches every experiment, every instrument, and every deadline, continuously, and writes a tamper-evident record as it goes.
Five ideas. One system that never stops watching.
Design
Lay out a protocol once in a typed step editor, timing, dependencies, and instrument I/O checked as you build it, then run it across as many experiments as you need.
Connect
Incubators, imagers, liquid handlers, and other lab hardware link in through a lightweight edge agent per system, so the platform always knows the true state of every instrument and sample.
Orchestrate
A scheduling engine sequences and times every step across every active experiment, like air-traffic control for your lab, so runs never collide.
Monitor
A single dashboard shows every experiment, instrument, and sample's status and location, with timelines and ETAs, flagging problems the moment they happen.
Trace
Every sample, measurement, and step is tracked end to end in a hash-chained, tamper-evident log, full lineage from source to result, for reproducibility and audit.
From a paper's methods section to a running experiment
Paste the materials & methods paragraph you're trying to reproduce. The assistant reads it as capability calls, not prose, and hands you a typed protocol ready to instantiate.
Paste the methods paragraph
Straight out of the publication, no reformatting. The assistant parses it for instruments, timing, and quantities.
The assistant reads it as capability calls
Every entity in the paragraph resolves to a typed node and a real, policy-checked write, not a guess it keeps to itself.
Nodes come out typed and connected
Ports are checked as they're wired, physical (plate/sample), data, and variable (dose, timing) don't cross, so a mis-mapped edge fails at design time, not on the bench.
Instantiate it, watch it run
One capability call turns the protocol into a live experiment on the real schedule, sequenced against everything else already running.
Every instrument, one surface. Every AI action, one leash.
Instruments plug in through the same control surface a material-handling system would use. An AI assistant is welcome to drive it, through the exact same door as everyone else.
MHS-style device integration
Every instrument, whether it's a liquid handler, an incubator, or a mobile relocation robot, speaks the same out-of-band control surface: describe, run a procedure, read a live state key, write a setpoint. One path, callable identically from the UI, the REST API, MCP, or an edge-agent script, and validated on every call against the instrument's own self-reported procedure list and safety envelope. Heterogeneous fleets slot in without bespoke glue code per vendor.
Agentic control, on a leash
The built-in assistant doesn't get a side channel: it calls the same policy-checked, event-sourced capabilities a person does, over MCP tool-calling, one registry, no shadow API. Every AI write is checked against your access rules, deferred for a human's approval when it touches something sensitive, like moving a plate, and logged as an action taken on behalf of a specific person. "The AI did it" is never where the audit trail ends.
A few more things quietly doing the work
Ontology-linked catalog
Compounds, treatments, and conditions linked to the standard vocabularies (OBI, RO, PROV-O) your other systems already speak.
Sample lineage
Every sample, plate, and well traced back through every derivation, pool, split, and transfer, all the way to its source, with a unique accession ID for life.
Reagent registry
Every working reagent traced back to its source lot, concentration, and expiry.
Consumable registry
Every plate, tube, and kit tracked well by well, from the moment it's registered to the moment it's discarded.
Data & screen explorers
Query results like a spreadsheet, plot them like a scientist, and turn a compound screen into viability, Z'-factor, and dose-response fits automatically.
Edge-agent fleet
One lightweight agent per system bridges every instrument to the platform, driver-connected or run by hand, with no single point of failure across the fleet.
Compliance & audit trail
A hash-chained, externally anchored event log; role- and rule-based access control with separation-of-duties and time-boxed break-glass overrides; and one-click FAIR evidence packages (RO-Crate + PROV-JSON) for every project.
What changes once the lab runs itself
Less manual coordination
Fewer handoffs between spreadsheets, chat threads, and instrument screens, and fewer errors that come from doing it by hand.
Faster experiment throughput
Continuous, automatic sequencing keeps your work moving instead of waiting on the next person to notice it's ready.
Higher instrument utilization
Every instrument's real capacity is known and booked precisely, so expensive equipment sits idle less often.
Audit-ready by default
A hash-chained, externally anchored event log and full lineage are captured as a byproduct of running the work, not a separate task afterward.
Grows with your lab
Start with a single instrument and expand to a full automated fleet on the same system, without re-platforming.
Works with what you own
Built to connect heterogeneous instrument fleets, no rip-and-replace, no single-vendor lock-in.
Research labs running real experiments, not just single assays: high-throughput compound screening, longitudinal culture studies, multi-step sample-prep pipelines, and regulated clinical workflows, each with its own instruments, timing, dependencies, and compliance requirements.
Ready to see your lab run itself?
We're onboarding a small number of research labs ahead of general availability.