Experimental intelligence · protein workflow launch

Learn from every experiment.
Know what to try next.

AttemptDB turns successful, unsuccessful, negative, and inconclusive experimental attempts into structured decision support—starting with protein expression and purification across different expression systems.

Check my experiment

Has this already been tried?

Compare your planned expression or purification conditions with structured historical attempts, outcome rates, and Context Match.

Rescue my experiment

What changed when similar failures worked?

Surface direct rescue links first, then evidence-supported alternatives and clearly labeled hypotheses.

Design my next experiment

What should I test next?

Generate a small, evidence-traceable follow-up matrix optimized for minimal change, success, diagnosis, or learning.

Initial technique focus

Protein expression → purification.

Start with mammalian, bacterial, yeast, insect-cell, and cell-free expression, then compare downstream purification strategies across systems.

First technique set

Expression systems first. Purification follows the protein.

Mammalian

HEK293 / Expi293F, CHO / ExpiCHO and related transient or stable expression workflows.

Microbial & yeast

E. coli, Komagataella/Pichia and Saccharomyces expression with host-specific recovery and purification context.

Insect & cell-free

Baculovirus/insect-cell and cell-free systems, connected to downstream affinity, ion-exchange, HIC, SEC and multistep purification.

How the evidence layer works

Conditions are data

Technique, expression system, target, concentrations, temperature, time, controls and other parameters remain searchable and comparable—not buried in prose.

Failure → rescue is a relationship

AttemptDB distinguishes verified RESCUES links from ordinary correlations, plus SUPPORTS, CONTRADICTS, REPLICATES and EXTENDS.

Recommendations show their work

Every suggestion carries supporting attempts, Evidence Strength, Context Match and a recommendation class. When evidence is missing, the system says so.

Literature ingestion pipeline

Reconstruct experimental space from papers.

Discover open-access papers, enforce a commercial-reuse license gate, stage machine-readable XML, detect candidate Experimental Series, and quarantine every extraction for review before it can enter the Attempt graph.

Open literature ingestion
Scientific guardrail

A failed experiment is not a failed hypothesis.

The platform preserves controls, replication, provenance, context and contradictory evidence so a result is not overgeneralized beyond the conditions that produced it.