Backed byCombinator
VALIDATION5 errors·4 warnings
Compilation0s
Reading protocol…
RT-qPCR · Gene ExpressionEditing…

Set up the RT-qPCR plate at a 2× master-mix

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Infera compilerreading
01Plain English

Set up the RT-qPCR plate at a 2× master mix. Combine 10 µL SYBR mix with each primer pair, then vortex briefly and spin down before loading. Add 2 µL cDNA per well, seal, and run the standard cycling program.

You describe the run in plain English — vague phrases and all.

Compressed for your screen — open on desktop for the full interactive compiler.

An AI-native compiler for the lab

The operating system for your laboratory.

Infera turns an experiment you describe in plain English into a validated, instrument-ready run — on the instruments you own, or by hand at the bench.

Learn more
// problem

Your instruments aren't the bottleneck. Getting a run onto them is.

Labs hold millions in instruments that sit half-idle. Not because the hardware can't do the work, but because every run starts with a full day of turning plain English into machine instructions.

Protocols are written for people, not machines. A scientist fills in the gaps from experience; an instrument needs every value named. So the translation happens by hand, every run.

What a machine can't read
01
“until the solution runs clear”
Humans watch and wait. Robots need a number, and nobody wrote one down.
02
“mix gently”
“Gently” isn’t a setting. Too fast shears the sample; too slow won’t mix. A robot needs an exact rate.
03
“incubate overnight”
Twelve hours or eighteen? Every downstream step inherits the drift.
04
“transfer the supernatant”
How much, and how much to leave? Disturb the pellet and the prep is ruined. The volume was never specified.
// how it works

The model only reads. The rest is deterministic.

Deterministic means fixed and checkable — the same description always compiles to the same run.

AI reads
Plain English
you describe
AI reads
Parse
model reads intent
Deterministic
Validate · Compile
checked + reproducible
Deterministic
Execute · Audit
runs on your instruments
AI reads
01
Plain English
you describe
02
Parse
model reads intent
Deterministic
03
Validate · Compile
checked + reproducible
04
Execute · Audit
runs on your instruments

One interface across your liquid handlers, plate readers, thermocyclers, and more.

What every run leaves behind
01

Validated before it runs

Dead ends, timing conflicts, and deck collisions are caught before a single tip moves.

02

Reusable across the lab

Every validated run becomes a template your team can rerun, checked against live inventory.

03

Yours when people leave

The protocol and its full history stay in the lab. New hires inherit exactly how each run was done.

// setup

Less time. Less waste.

Setting up a run used to take a day with the vendor's manual, naming every value by hand. Infera already knows your instruments, so the same run is ready in minutes.

And because every step is checked against your deck and inventory first, nothing gets burned on a run that was going to fail anyway.

Pre-flight check · RT-qPCR 9 caught
Deck & labware resolvedauto
Tip racks, plates, and reagents mapped to the deck automatically.
“run the standard cycling program”fixed
Cycling was never specified — set to 40 cycles · 95/60 °C.
“vortex briefly and spin down”fixed
No time given — set to 3 s vortex, 10 s spin before load.
Tip collision at A4fixed
The path would have crashed mid-run — rerouted before a tip moved.
Volumes checked vs. inventoryok
Every step has enough reagent on hand. Nothing starts short.
9 issues caught and fixed before a reagent was spent.
// integrations

One interface, not one platform.

Your instruments, any vendorLab Mode

Every instrument ships its own closed software, and your lab runs a mix. Infera's protocol layer is hardware-agnostic — describe the run once and it targets whatever you own, across the full range of instruments and every vendor.

Liquid handlers
Plate readers
Mass specs
Thermocyclers
Centrifuges
Bring your protocols in
ELNs & docsConfigure

Sync from Benchling, PDFs, Google Drive, Dropbox, wherever your research lives.

Data ConnectorsConfigure

Auto-detect instrument format, map columns, set QC thresholds.

Infera GatewayConnected

Auto-upload from the instrument PC. No manual export.

Keep the lab in the loop
AlertsConnected

Email, text, or Slack the moment a protocol fails validation.

InventoryConnected

Track reagents and consumables, flag low stock, and reorder before you run short.

// at the bench

Even the steps you do by hand.

Not every step runs on a robot. Pipetting, gels, fermentation by hand — Infera tracks those too: what step you're on, what goes where, and what could go wrong before you do it.

So the record stays complete, even when no instrument was ever involved.

Manual stepby hand
Step 14 of 22
Add 600 µL ethyl acetate:cyclohexane, invert to mix
Plate A1, working at the bench · not on an instrument
Internal standard not yet logged. Confirm before the next step.
Logged to the run record automatically.

Let's build this together.

Harvard + Caltech team, YC P26, out to bring real automation to every wet lab. If your team burns time turning protocols into machine code, let’s talk.

Talk to the team
Early access

Request access

We're onboarding a handful of labs as pilots. Tell us about your setup, including any instrument you don't see listed, and we'll reach out.

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