SYNAPSE LABS

For most of history,
one expert could only
be in one place at a time.

One hypothesis. One machine. One experiment at a time.

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Objective

Find plausible variants explaining this phenotype.

ws-7f3a @ 4e91c0 · ready

Forking ws-7f3a @ 4e91c0 · same environment, data and files · different hypotheses

What if the laboratory were elastic?

Every branch begins from the same exact technical state.
Different hypotheses can now be tested independently.

Synapse Workstation

Your autonomous R&D lab.

Give Synapse an objective. It works across real scientific and engineering tools, explores promising approaches in parallel, verifies the results, and keeps working when you leave.

Each branch is a real, isolated environment.
One changes a preprocessing step. One changes a parameter. Another tries a different model. Another takes a different approach entirely.

Some fail. Some stop early. Some produce something strange. A few produce something promising.

The scarce thing is no longer execution. The scarce thing is deciding what deserves attention.

Three worlds of R&D

Life

Genomics · RNA-seq · Single-cell · Variant interpretation

Hundreds of candidate analyses.
Most disappear. A few survive.

Machines

CAD · CFD · FEA · Thermal · Optimization

Geometries branch from a common design.
Some fail constraints. Some outperform. A few return for review.

Silicon

PCB · FPGA · EDA · Verification

Schematic, simulation, verification, iteration.
Many possibilities. Very few conclusions.

Not one category of software.
The actual environments where research and engineering happen.

Civilization is built from accumulated experiments.

Progress depends on what we can afford to try.

Productive capacity depends not only on how many people work, but on the tools behind each of them. A scientist with a computer explores more than one with paper. An engineer with simulation explores more than one who must build every prototype.

One expert can command a much larger experimental surface.

Expert judgment × experimental capacity → technical progress

One objective. A hundred attempts. Three decisions.

Synapse makes it possible for one expert to supervise far more independent technical exploration than they could execute by hand.

The expert remains responsible for judgment. AI expands the search.

100 branches returned. Plots, simulations, logs, measurements, failures.

Checked against explicit criteria.

Failures removed.

Duplicates collapse. Weak evidence recedes.

Related findings merge.

Three things need your judgment.

  1. Lead Loss-of-function variant in a candidate gene Three independent lines of evidence · 41 branches agree
  2. Conflict Branches disagree on a structural variant Assembly-based branches see a deletion; alignment-based branches do not
  3. Follow-up The phenotype may also be regulatory Weak upstream signal · one experiment proposed, not yet run

Execution expands. Attention does not.

A farmer gained a tractor. A machinist gained CNC. An engineer gained CAD. A scientist gained computation. Now one expert gains an elastic population of workstations.

Every technological era gives people new leverage.

The computer gave every knowledge worker a machine.

Synapse gives one expert a laboratory.

Modern life rests on systems someone had to design, test and improve.

What changes when experimentation becomes abundant?

Most of the possible world has never been tried.

Lower the cost of trying, and the frontier moves.

Experiment. Verify. Remember. Build again.

The laboratory gets better at being a laboratory.

Successes, failures, artifacts, evidence and methods persist. Each generation begins with more than the last.

You used to have one computer.

Now you have an entire technical organization.

Synapse Workstation

Your autonomous R&D lab.

Works in its own computer.
Real genomics, CAD, simulation, and EDA tools, already configured.
Keeps working when you leave.
Long-running experiments continue in the cloud.
Explores more than one answer.
Synapse branches into competing methods, designs, and hypotheses.
Verifies before it reports back.
Simulation, tests, and domain-specific checks filter bad results.
Brings you what needs judgment.
You review the frontier, not 100 agent sessions.

Objective → verified result.

The next experiment is waiting.