The Edge-First Scientific Data Platform for Modern Labs
OVERVIEW
Veritas Automata delivers an edge-first scientific data platform that enables modern laboratories to scale automation, protect data integrity, and adopt AI without disrupting operations.
This approach connects how instruments, data, infrastructure, and teams work together so the lab can function as a system rather than a collection of tools.
The Problem We Solve
Many labs expand instruments, software, and workflows without aligning on how data should be governed and trusted across the environment. This leads to fragile ingestion, siloed systems, stalled analytics, and growing compliance risk.
These challenges are not caused by a lack of technology. They are caused by how the lab operates.
Our Solution
An edge-first foundation that provides:
- Deterministic ingestion from instruments and automation systems
- Local compute and tiered storage so experiments never depend on the cloud
- Built-in data lineage and auditability from raw file to derived insight
- Controlled cloud synchronization for analytics and AI
- Alignment with 21 CFR Part 11, EU Annex 11, GAMP 5, ISO 27001, and ALCOA+
This is infrastructure designed to support how science should work.
What This Enables
Trusted data from
instrument to archive
instrument to archive
Reduced inspection
and audit risk
and audit risk
Predictable scaling
across rigs, labs, and sites
across rigs, labs, and sites
Fewer manual workarounds
and scripts
and scripts
A safe, incremental path
to AI and advanced analytics
to AI and advanced analytics
How We Work
We begin by understanding how the lab operates today across people, process, instruments, and data. From there, we design a reference model, prove it through a focused pilot, and scale it into a lab standard.
No disruption.
No rip and replace.
No rip and replace.
Frequently Asked Questions
Do we need to replace our instruments?
No. This platform is vendor-agnostic and designed to work with existing equipment and automation.
Does this require moving to the cloud?
No. The platform is edge-first. Cloud integration is controlled and optional.
Is this only for regulated labs?
No. It supports early discovery, translational research, regulated development, and manufacturing environments.
Is this a large disruptive project?
No. Engagement begins with alignment and a small pilot before any broader commitment.
How long does a pilot take?
A typical pilot can be completed in approximately 90 days.
How does this support AI initiatives?
By ensuring data is consistent, governed, and trusted before analytics or AI models are introduced.
How does this improve compliance posture?
Data integrity, lineage, audit trails, and retention controls are built into the architecture rather than added later.
Can this scale across multiple labs or sites?
Yes. The architecture is designed to be repeatable and extensible across rigs, labs, and locations.