Pharma and biotech engineering
Forward-deployed scientific software engineering
LabACT is a small team of experienced engineers working directly with biopharma teams. We use a practical scientific method: observe the work, form a useful hypothesis, test it with a focused build, measure the result, and expand what proves valuable. We automate workflows and build approval systems, document operations, research pipelines, scientist portals, monitored data systems, integrations, and internal tools, includingLaboratory Automationprojects.
Probabilistic tools. Deterministic systems.
Automation
Turn useful improvements into working software
Collaboration
Work alongside the people who run the process
Transformation
Expand what proves valuable across the organization
Our engineers work alongside biopharma teams to build and improve the systems behind regulated work, from document review and research pipelines to approvals, integrations, and internal operations.
Our specializations are Automation, Collaboration, and Transformation. We start with useful automation, work alongside your team, and expand what proves valuable. We work alongside your team until it can run and extend the system on its own. Projects can start with a manual process, a spreadsheet, an AI prototype, or a system that no longer fits the work.
This model also guides our work in Laboratory Automation: automate a useful laboratory task, collaborate with the scientists and operators who use it, then transform the improvement into a dependable system.
One QC group had a ChatGPT workflow that helped reviewers but could not support an audit. We rebuilt it in the cloud environment the group already used, using technologies its team could support, with signed approvals and a complete audit log. The reviewers kept the useful part, and the team gained a system it could control.
Across many biopharma organizations, we have seen the same challenges repeat for decades: fragmented spreadsheet workflows, individual workarounds, and tools that help one group but cannot scale or pass an audit. Now scientists are prototyping with ChatGPT, Claude, Copilot, and similar tools—and more than ever, durable solutions can be built collaboratively with the people who run the work.
We help turn those local AI experiments into reliable systems on your company IT infrastructure: shared access, SSO through Okta or your identity provider, and the surrounding software for security, approvals, and auditability—so useful ideas become systems the organization can operate and extend.
We help teams understand a difficult workflow, build the right software around it, and take ownership when the work is complete.
Our engineers work with leadership, domain experts, engineers, and operators to understand the current process and improve it. Common work includes approval workflows, document review, research software, scientist portals, clinical trial competitive intelligence, data movement, external-source monitoring, service triage, and automating spreadsheet-and-email handoffs.
We build internal applications, automations, integrations, and research pipelines. Depending on the job, that can include CDD APIs, structured exports to Postgres, data ingestion, scheduled orchestration, queues, permissions, audit logs, review inboxes, provenance, scientist-facing views, and model-assisted extraction.
Your team receives source code, documentation, tests, deployment tooling, monitoring, runbooks, and a clear path for future changes. We can also establish engineering standards for using AI without making operations depend on an uncontrolled runtime.
Applications that connect your records, business rules, AI-assisted steps, and people.
For example, a batch-record review can pull PDFs from a shared drive, extract fields, write structured results to Postgres, route exceptions through an approval queue, and log every state change. The same pattern applies to research data, service requests, quality records, and other repeatable work. Other systems may combine external registry or source monitoring, scheduled data sync, operational status views, and scientist-facing workbenches. A CDD API can feed structured inputs and exports into Postgres, where materialized reports stay current and can support custom applications, MCP tools, and controlled AI chat. Production delivery can use managed AWS services such as CloudFormation, Rain, EventBridge, Lambda, and ECR, with deployment checks, monitoring, and runbooks around them. The same pattern supports clinical trial competitive intelligence: custom searches, scheduled source ingestion, normalized data, current reports, and immediate alerts.
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Layer 2
Layer 3
Layer 4
AI can help with extraction, classification, summarization, drafting, and anomaly detection. Your application still handles data, rules, permissions, approvals, provenance, monitoring, and the record of what happened. Exported data can also support a measured machine learning loop with versioned features, labels, evaluations, and feedback.
Choose the starting point that matches your workflow, system, or team.
Map the current process, tools, data, blockers, risks, and ownership. Decide what to automate, where current technology can help, and what stays under human control.
What you get
Technical and operational transformation plan
Build the application, automation, integration, research pipeline, scientist portal, competitive intelligence system, or internal tool. We use current technology to move quickly, then ship maintainable software your team can operate.
What you get
Working code, AWS infrastructure, tests, deployment tooling, documentation, monitoring, and current reports
Test and automate a promising workflow, data process, spreadsheet, n8n workflow, or manual process, then turn the result into a reliable production system.
What you get
Source-controlled, testable, production-grade automation
Help internal teams use current technology in engineering without letting operations turn into an uncontrolled runtime.
What you get
Standards, examples, review processes, reusable components, training, and ownership transfer
We help regulated teams move from an idea or a stuck process to software that supports the work and belongs to the team running it.
Lab is where you explore. ACT is where you automate, collaborate, and transform the work.
Practical notes on reproducible research software and turning promising corporate AI use cases into measurable, owned systems for pharma, biotech, and regulated work.
A practical architecture for custom trial searches, source ingestion, analyst review, current reports, and immediate alerts.
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A practical architecture for structured compound data, current reports, AI-assisted analysis, and applications built on exported data.
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How to make analysis scripts, notebooks, and research workflows easier for another scientist to rerun and check.
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A practical look at repeatable AI opportunities, useful measures, and the parts of the work software must own.
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Turn a useful prompt into code, tests, interfaces, and operations.
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Where agents help, where they fail, and when to replace them with software.
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Architecture patterns for AI-assisted systems with hard boundaries.
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What belongs in databases, code, AI, and human review.
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Turn repetitive work into client-owned software.
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Versioning, evaluation, approvals, logs, retries, and security gates.
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Forward-deployed scientific software engineering
A small team of experienced engineers for biopharma teams
We work directly with small and large biopharma organizations to build new systems and improve the ones they already depend on.
Our work covers scientific software, research pipelines, approval workflows, document review, scientist portals, data integrations, external-source monitoring, and internal tools where audit trails, data integrity, and operational reliability matter.
We bring senior engineering experience and use current technology where it improves the work. The result is source-controlled, tested software with deployment tooling, monitoring, and runbooks that your team can operate and extend.
Get in touch
A workflow worth improving, a result worth testing, or an existing system that needs experienced engineers working alongside your team.
hello@labact.com