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Build vs buy

Build or buy your ELN and LIMS?

Building your own can be fun, and it fits your science. Maintaining it is not fun, and over the years it's where most of the cost and time go. Cypher AI gives you the fit of building without maintaining it yourself.

By the Cypher AI team · Updated October 20, 2026

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After the first version

What does it take to maintain your own ELN and LIMS?

The first version is a database and some forms. Maintaining it means all of this, for as long as the lab uses it.

Audit trail and sign-offWho changed each sample record and when, and signatures on ELN entries.
PermissionsWho can see, edit and approve each project, kept current as people join and leave.
Backups and recoveryRestores you have tested, and deleted records you can bring back.
Security reviewsQuestionnaires from partners, and an audit once a pharma partner asks for one.
Changes as the science movesNew assays, sample types and instruments. Each one is engineering work.
Someone on callFixes, upgrades and outages, and a plan for when the person who built it leaves.

Building with AI

Can you build your own LIMS with Claude or ChatGPT?

You can build a first version. Coding agents such as Claude Code and OpenAI Codex write working database code quickly, and Anthropic and OpenAI both now offer tools for scientists. However, neither offers a LIMS: one shared record of the lab's samples, where they are and what was done to them.

AI speeds up the building. It doesn't do the maintaining: your team still hosts the code, secures it, checks its results and fixes what breaks. The checking is the hard part. For example, one proteomics researcher found an AI-built tool changing the chart to match their feedback, rather than fixing the logic underneath.

Cypher AI puts the agent inside a system that already has the audit trail, permissions and backups. Ask for an analysis and it writes and runs Python you can read. Save it as a widget and the team reruns it on the next plate. Before the agent writes to the LIMS, it shows you a plan to approve.

At a glance

How do building and buying compare?

Build in-house
Buy a traditional ELN and LIMS
Cypher AI
Getting started
After the first round of building and testing
After schema design and an implementation project
Ready to use on day one
Fit to your science
Built around your workflow
The vendor's data model
Add LIMS fields, material types and plate layouts as the work changes
Changing it
Engineering time and testing for each change
An admin or a vendor request
Scientists add LIMS fields; the agent builds analyses and widgets
Audit trail and sign-off
Yours to build and test
Included
Every LIMS change is logged; ELN entries can require a signature and can't be edited during review
Security
You build your own controls and audits
The vendor's certifications
SOC 2 Type II; Enterprise runs in your cloud account
AI
Whatever you connect yourself. You call the model and design the harness
Varies by vendor
A tested and tuned harness: one agent across the ELN, LIMS and analysis that asks before it writes to the LIMS
Upkeep
Your team, for as long as it runs
On the vendor's release schedule
Handled by Cypher AI; feedback goes straight to the people who build it
Your data
On systems you run
In the vendor's cloud; export varies
Export options in the UI, a REST API, and your own cloud on Enterprise
Cost
Mostly maintenance, and it grows with the lab
License, implementation and add-ons
Per-user plans with the ELN, LIMS and agent included; Enterprise priced per team

"Traditional ELN and LIMS" describes the common pattern, not any one product.

The hard part

Why is the LIMS the hardest part to build?

The ELN records what happened in each experiment. The LIMS runs on a data model: what each sample is, which came from which, how much is left, which reading belongs to which well. That model is difficult to get right, and hard to change once data is in it. Cypher AI's LIMS comes with the model built, and scientists add fields as the work changes.

  • Samples in an ELN entry become LIMS records after you approve them.
  • Plate reader results land on the right wells and show as a heat map.
  • Each sample traces back to its source, and its volume goes down as you use it.
  • Every change to a sample is recorded: the old value, the new value, who changed it and when.

Best of both

The platform fits your science, and keeps getting better.

AI under your controlThe agent builds analyses, protocols and widgets from a plain request, and shows a plan before it writes to the LIMS.AI
Flexible LIMS dataAdd a field, a material type or a custom plate grid when the work changes. No schema to design first.
One connected systemELN entries, samples, readings, analyses, pipelines and outside orders link to each other.
A team that works with youYou talk directly to the people who build it, and Enterprise includes a forward-deployed engineer.
The platform improves quickly.Each change builds on a system that already works, so improvements reach your lab fast. Matching that pace in-house takes a dedicated engineering team.
The platform carries what other labs have learned.What we learn working with one lab goes into the product for every lab. An in-house system learns only from yours, one problem at a time.

Trade-offs

Which one fits your lab?

When does building make sense?

  • Software is part of your product.Your pipeline or platform is what you sell, and your engineers already maintain it.
  • No platform does the job.For example, control software for an instrument you designed.
  • You have engineers for the long run.For upkeep, security and support, not only the first version.

When does buying make sense?

  • Your team's time belongs on the science.Or on your product, rather than on a sample tracker.
  • Your records need to hold up to scrutiny.With partners, in a diligence review and in an audit.
  • Several people share samples and results.Freezers, plates and analyses that more than one scientist depends on.
  • You want AI that works with your lab's data.Without building the connections, permissions and review steps yourself.

Cost

What does it cost to build, and then to maintain?

You pay for building once. You pay for maintaining every year, and it grows with the lab: more users, assays and partner reviews, until running the system is someone's job.

CostHow oftenFigureSource
Building the first versionOnceWeeks to yearsWeeks for a basic sample tracker; more than two years for one academic lab's full LIMS. Source Code Biol Med, 2011; J Mol Diagn, 2018
Someone to run itEvery yearA part-time employeeKeeps one academic lab's in-house LIMS secure and up to date. J Mol Diagn, 2018
An engineer, as the lab growsEvery yearAbout $240,000Median pay for a software developer in Boston ($166,090, BLS, May 2025), with benefits (wages are 69.2% of total pay, BLS, June 2026); our arithmetic. Developers spend 17.3 of their 41.1 hours a week on maintenance. Stripe developer survey, 2018
A security auditEvery year$10,000 to $80,000+The independent audit partners ask for, plus staff time. Vendor estimate, Vanta

Buying moves most of this to the vendor. Cypher AI's plans are on the pricing page: Pro includes the ELN, LIMS and agent for each user, and Enterprise adds your own deployment and a forward-deployed engineer.

First steps

How do you get started?

  1. Create a free account.The ELN is free, with no card.
  2. Bring in a spreadsheet.On a free onboarding call, the agent turns your sample sheet into LIMS records you approve. The LIMS comes with Pro.
  3. Save your first widget.Ask the agent for the analysis your team runs most, then save it for the team.

Setting up for a larger R&D team? Enterprise runs in your own cloud account, and a forward-deployed engineer works with your team to set up your workflows and data integrations.

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FAQ

Questions about building or buying.

Can we use spreadsheets, Airtable or Notion as our ELN and LIMS?

Many small labs start there. Spreadsheets don't track sample lineage or who changed a value, and Excel's autoformat has turned gene names into dates in 30.9% of papers with Excel gene lists. One lab running its ELN in Notion and its LIMS in Airtable found the sync between them could stop for weeks without anyone noticing.

Does 21 CFR Part 11 apply if we build our own system?

Part 11 applies to the records, whoever wrote the software. If records fall under FDA predicate rules, such as GLP, GMP or clinical work, an in-house system needs validation, secure time-stamped audit trails, limited access, and trained people to develop and maintain it. Much early discovery work isn't covered. Cypher AI supports Part 11–style workflows: ELN entries can require an electronic signature and can't be edited during review, and the ELN and LIMS record every change, with who made it and when. Whether a process meets Part 11 depends on your own validation.

Can we keep the tools we've already built?

Yes. Widgets and scripts in Cypher AI read and write the LIMS through its REST API, Nextflow pipelines run from your own GitHub repositories, and your organization can connect its own predictive model and call it from the agent.

Can we move a homegrown sample tracker or spreadsheets into the Cypher AI LIMS?

Yes. Export your sample tables to CSV or Excel and give them to the Cypher AI agent. It proposes the samples, containers and plate positions to create, and with the default setting nothing is written to the LIMS until you approve the plan.

Do we keep control of our data if we buy?

Cypher AI doesn't use customer data to train AI models, its own or any third party's. LIMS readings export to CSV, Excel or Parquet, ELN entries to PDF, and LIMS records through the REST API. On Enterprise, Cypher AI runs in your own cloud account in the US, the EU or China.

How did we write this?

We make Cypher AI, so we aren't neutral on build vs buy. Figures about building come from the public sources listed here, checked on October 13, 2026. Cypher AI details come from cypherbio.ai and the product's documentation.

Spotted something out of date? Tell us at cypherbio.ai/contact and we'll fix it.

Sources

Product names are trademarks of their owners. Cypher AI isn't affiliated with or endorsed by the companies named on this page.

ELN

Where samples link into experiments.

LIMS

Samples, plates and lineage, ready on day one.

The AI Agent

It can act. You approve.

Data Analysis & Dashboards

Analyses your team reruns on the next plate.

Related reading

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