About MESSAI
We exist to unlock the microbial electrochemical revolution.
A small team building the discovery engine for a field that has spent two decades waiting for its knowledge to become computable — structured, queryable, and predictive, from literature to laboratory to scale.
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Our vision
A foundation the whole field can build on.
The vision
To make microbial electrochemistry as designable as any mature engineering discipline — by unifying and standardizing the world’s MES knowledge into one AI-powered platform for research, development, education, and commercialization.
The mission
To give researchers, engineers, and innovators the tools to design, simulate, and predict electrochemical systems grounded in the entire published record — not a handful of remembered papers — so good ideas reach the world faster.
Provenance first
Every value is linked to its source paper, and carries units and measurement conditions wherever the paper reports them. Where a field is missing we show it as missing rather than inferring it.
Honest uncertainty
Every prediction ships with a calibrated interval — never a point estimate dressed up as certainty.
Open by default
The core MESS packages — parameters, materials, datasets — are open source and community-usable.
Built between disciplines
MESSAI lives in the gap between biology, electrochemistry, and software — by design.
From research to innovation
How a discovery becomes an industry.
The distance between a brilliant result at the bench and a system running in the world has always been enormous — not because the science is weak, but because the knowledge never became something you could compute against. We see that distance as a pipeline, and we built MESSAI to make each stage flow into the next.
Literature
Two decades, tens of thousands of papers
The evidence already exists — scattered across hundreds of journals in incompatible formats, un-queryable and impossible to compute against.
Structure
Papers become data
AI reads every paper and extracts every measurement with its source, units, and conditions — harmonized to SI and a typed ontology of 835 parameters.
Predict
Data becomes foresight
Per-class models turn the corpus into performance predictions — each carrying a calibrated interval, a confidence, and a traceable source. Never a naked number.
Design
Foresight becomes a system
Researchers design, simulate, and sweep reactors in an interactive 3D lab — testing a hundred configurations in silico before touching a bench.
Deploy
A system becomes impact
Validated designs reach the world — cleaner water, green hydrogen, carbon turned to chemicals — and every result flows back to sharpen the data that produced it.
The unlock
The bottleneck was never the biology.
For twenty years the science has worked. Microbes have been turning wastewater into electricity, organic waste into hydrogen, and carbon dioxide into chemicals in labs around the world. What the field lacked was not another breakthrough at the bench — it lacked the infrastructure to make those breakthroughs cumulative.
Until recently, no technology could reliably read the messy, heterogeneous text of scientific papers and turn it into structured, comparable data — not at the accuracy or cost a real platform demands. That is precisely what modern AI now does. It reads the whole field at once, extracts every measurement with its provenance, and makes the results computable for the first time.
AI collapses the decade-long lag between a result in a lab notebook and a design an engineer can build — and that is what turns a promising science into a deployable industry.
That is how we believe the microbial electrochemical revolution gets unlocked: not by one lab out-discovering the rest, but by giving the whole field a shared, evidence-based foundation to compound on.
Platform figures as of May 2026 — effectively the entire historical MES literature.
The team
Founder, scientist, operator.
The combination this category requires: platform engineering, peer-reviewed domain authority, and disciplined research operations.
Sam Frons
Founder & CEO
Information-infrastructure builder across health, agriculture, and climate. Spent six years mapping the MES field before building the platform.
Zakiya Sharpe
Head of Research Operations
Runs the extraction QC and validation workflows that keep the corpus trustworthy — every measurement traced from paper to queryable record.
Dr. Lane Gilchrist
Chief Scientific Officer
Bioprocess engineer and faculty scientist — the peer-reviewed, bench-side authority anchoring the parameter ontology and scientific direction.
Questions
Frequently asked.
What is MESSAI?
MESSAI is the intelligence layer for microbial electrochemical systems (MES). We turn two decades of published research into structured, queryable, predictive infrastructure — spanning literature search, a typed parameter ontology, an interactive 3D design lab, and performance predictions with honest uncertainty.
What are microbial electrochemical systems?
They are reactors where microbes growing on conductive electrodes drive electrochemical reactions — generating electricity from wastewater, producing hydrogen from organic waste, or synthesizing chemicals from CO₂. Microbial fuel cells (MFC), electrolysis cells (MEC), and desalination cells (MDC) are the best-known members of a much larger family.
Where does your data come from — and can I trust it?
Every value is extracted from the published literature and carried with its full provenance: the source paper, the units, the measurement conditions, and a confidence score. Nothing enters the ontology without its source attached, and incompatible units are harmonized to SI so studies can finally be compared like-for-like. MES data has enormous natural spread, so we treat scientific honesty as a rule, not a footnote.
How accurate are the predictions?
Every prediction ships as a value, a unit, a calibrated confidence interval, a confidence score, and a traceable source — never a bare point estimate. Corpus-wide variance in these systems runs to four figures, so a single headline number would be a fiction. We show you the range and where it came from.
Does MESSAI build reactors or hardware?
No. We are the intelligence and software layer that maps, models, and predicts these systems. We don’t build or sell the hardware — we make it far cheaper and faster to design the hardware that works.
Is any of it open source?
Yes. The core MESS packages — parameters, materials, datasets, and more — are open source and community-usable. The platform is built on the belief that a field advances fastest on shared, open foundations.
How do I get started?
Explore the research intelligence surface, try the 3D lab, or browse the parameter catalog — all public. To talk about a partnership or a pilot, email founders@messai.io.