Capture everything
Drop in spreadsheets, instrument exports (XRD, SEM, spectroscopy, sensor logs), PDFs, reports, and lab notebooks. Zutra classifies and parses each file automatically — no templates to fill in.
New — Drop in raw instrument files, scripts, and whole folders. Zutra structures them for you.Learn more
The institutional memory of R&D
Every result, decision, benchmark, and dead end your lab produces — captured, structured, searchable, and governed. Knowledge compounds instead of walking out the door.
Capture (lab)Explore (analysis)
What are you working on?
Capture a result from the bench, or ask a question across everything your lab has measured.
M-042 looks different after the 600 °C anneal — here's the XRD…
Agent sees only data you're cleared for · scoped server-side
Built for R&D labs in materials, chemicals, semiconductors, and advanced manufacturing — and the universities and research institutes working alongside them.
Materials scienceChemicals & formulationSemiconductorsAdvanced manufacturingBiotech & life sciencesUniversities & RTOsMaterials scienceChemicals & formulationSemiconductorsAdvanced manufacturingBiotech & life sciencesUniversities & RTOs
How it works
From raw files to answers — without a data team
Structure automatically
AI maps messy column names, units, and naming conventions into one consistent schema. Every measurement becomes queryable — no manual cleanup, no schema design.
Ask in plain language
Question your entire dataset in plain English. Zutra writes the SQL, runs it read-only, and shows the chart, the numbers, and the exact query behind them.
Why R&D labs choose Zutra
Knowledge that compounds instead of walking out the door.
Batch M-042 · 600 °C annealFailed
Batch M-038 · 620 °C annealPassed
Batch M-031 · 580 °C annealPassed
Every result, in context
Bench results, failed runs, and the reasoning behind each decision live in one searchable record — not in someone's notebook or their head.
"What yield did we get at 650 °C last quarter?"
Ask across everything you've measured
"What yield did we get at 650 °C last quarter?" returns an answer with the data and the query behind it — across every experiment your lab has run.
.xrd.sem.csv.pdf.xlsx.json
Any instrument, any file
XRD, SEM, spectroscopy, sensor logs, Excel, PDFs. Zutra parses the formats other tools choke on, with an extensible parser library for new ones.
Dr. PatelLab lead · full access
J. KimResearcher · project scope
M. OseiIntern · read-only
Governed by default
Row-level access, full audit trail, read-only queries. Every person sees only the data they're cleared for — scoped server-side.
raw_xrd.dat
parse()
schema
94.2%
Reproducible and traceable
Every number traces back to its source file, transformation, and query. Lineage you can defend in a design review or an audit.
CSV
Parquet
Your cloud
Your data stays yours
Export to CSV or Parquet anytime. Deploy in your own environment, bring your own keys. No lock-in.
Compatibility
Works with your instruments, files, and systems — not against them
XRD exportSensor logLab reportExcel sheetPDF
Reads what your lab already produces
Instrument exports, spreadsheets, documents, and whole folder dumps — ingested as-is. No reformatting, no rigid templates.
SSO / SAMLS3 / GCS / AzureCSV · Parquet · API
Fits your existing stack
SSO / SAML sign-in, your own object storage, and export to the analysis tools your scientists already use.
Your VPCBYO keysNo egress
Your environment, your control
Deploy in your own cloud or VPC, bring your own encryption keys, and keep raw data where it lives.
Natural language queries
What scientists ask Zutra
Plain-English questions. Real answers, with the data and query behind them.
“Why did this batch fail after the final heat-treatment step?”
“Compare performance across every batch this quarter and flag anything below spec.”
“Find every experiment that used the new material — and what we concluded.”
“Which process conditions gave the most consistent results last year?”
“Compare yield across all high-temperature runs in the last six months.”
“What did we learn from the failed trials in Q2?”
The knowledge problem in R&D
R&D generates enormous value — and quietly loses most of it. Results sit in personal notebooks, raw files on shared drives, and the memory of whoever ran the experiment. When they move on, it goes with them.
Labs re-run experiments someone already did, and hard-won negative results vanish. The knowledge exists — it just isn't structured, searchable, or shared.
Zutra captures every result, decision, and dead end as it happens — structured, searchable, and governed — so your institutional knowledge compounds instead of leaking out the door.
From the lab
Notes from the R&D data frontier
An occasional note on managing experimental data, lab knowledge, and using AI for research. No spam.
Stop losing what your lab already knows.
See Zutra on your own data, or start exploring in the app.