01
Intelligence
AI that shows its evidence.
When knowledge is scattered across documents and systems, we build retrieval, extraction and agent workflows that point to their sources and stop for human approval.
Technology partner for life sciences
Complex science in.
Working systems out.
AI, software and cloud engineering for Pharma, Biotech, Healthcare, Medtech, Diagnostics
What we do
One partner.
Three layers of engineering.
Most life sciences technology problems cross all three. We take responsibility for the layers your project needs, and make them work as one system.
02
Applications
Software shaped around the lab, the plant and the clinic.
When work moves between spreadsheets, inboxes and disconnected systems, we build the portals, internal tools and integrations that put status and handoffs in one place.
03
Foundation
Cloud that is secure, reliable and ready for validation.
When scientific applications have to run every day, we provide the environments, release pipelines, monitoring and security controls that keep them dependable.
Where we help
Problems we are
built to solve.
Each starts as one bounded workflow, with the people accountable for it.
10 problems
- Pharma
- Biotech
- Medtech
Find the approved procedure, with its source
Teams spend time locating the current version of a procedure and checking it is the approved one.
What we buildA knowledge assistant over approved SOPs and technical files that answers with references, respects document versions and flags missing evidence for review.
- Pharma
- Medtech
Prepare quality review packs for people to assess
Collecting records for a quality or operational review is manual, repetitive and easy to leave incomplete.
What we buildAn agent that gathers material from approved systems, lists what is missing and assembles a review pack. The release decision stays with the reviewer.
- Diagnostics
- Healthcare
One view from request to report
Request, specimen and report status sit in separate systems, so exceptions surface late.
What we buildAn operations portal that connects available system interfaces, routes missing information and shows status and exceptions in one place.
- Biotech
- Pharma
Reproducible analysis environments
Analyses are hard to repeat when environments, data access and versions drift between researchers.
What we buildVersion-controlled cloud environments with controlled data access, separated development and production, and repeatable releases.
- Biotech
- Diagnostics
Laboratory data that arrives ready to use
Instrument exports and research records are copied by hand into the tools that analyse them.
What we buildData pipelines that collect, validate and organise laboratory outputs with lineage, then expose them to analysis and reporting applications.
- Biotech
- Pharma
Triage scientific literature for expert review
Scientists cannot read everything that might matter to a programme.
What we buildClassification and summarisation of incoming publications against agreed criteria, each summary linked to its source for scientist review.
- Healthcare
- Diagnostics
Route administrative requests to the right owner
Requests arrive by email and forms, then wait for someone to decide who should act.
What we buildAn intake workflow that classifies requests, assigns an accountable owner, tracks approvals and makes exceptions visible.
- Medtech
Service portals around medical technology
Product, service and support teams lack one application connected to the platform behind the device.
What we buildA service and operations portal connected to approved device or platform interfaces through secure cloud services.
- Medtech
- Pharma
Releases that produce their own evidence
Release records, approvals and access changes are reconstructed after the fact.
What we buildVersion-controlled pipelines with security checks and least-privilege access that record what was released, when and by whom.
- Diagnostics
- Healthcare
- Medtech
A reliability baseline for essential portals
Teams learn about slow or failing services from their users.
What we buildAgreed reliability targets, useful dashboards, routed alerts and rehearsed recovery runbooks for the services that matter most.
How we work
From first question
to everyday use.
Start with a focused assessment, pilot or implementation. Expand on the basis of what the work demonstrates.
Define the intended use
Map the people, data and systems involved. Choose a bounded problem and agree what a useful result looks like.
Test with your experts
Use representative examples to check the critical assumptions. Agree review responsibilities and acceptance criteria.
Engineer the system
Build the application and its integrations. Test permissions, everyday use, exceptions and failure recovery.
Put it into operation
Deploy with monitoring, documentation and a practical handover. Scope ongoing support around your operating needs.
Why Zeltar
What you can
hold us to.
Science informs the questions. Engineering builds the answer. These commitments shape every engagement, whatever its size.
Evidence before confidence
Outputs show their sources. Quality is measured against representative cases, not the fluency of a demonstration.
People keep the decision
Review and approval are designed into the workflow. Clinical and quality judgement stays with authorised professionals.
Validation-aware from day one
Intended use, data access and validation responsibilities are agreed with your quality and domain teams before the build.
Insights
Scope it before you build it.
How to evaluate an AI knowledge assistant
Define approved sources, representative questions, evidence checks and human review before commissioning an assistant over SOPs or technical documents.
Read the guideHow to scope a workflow automation project
Map one process from trigger to completion, including approvals, duplicate requests, failed updates and the person who owns each exception.
Read the guideWhat a cloud deployment handover should include
Agree what the operating team needs to release, observe, recover and pay for an application or API after deployment.
Read the guideStart a conversation
What needs to
work better?
Tell us about one workflow, application or technical challenge. Include your sector, current systems and the outcome your team needs.
Keep this first conversation high level. Please leave patient information, confidential research and sensitive documents out of the form.