Testimonials
Proof in
production.
We value the feedback our customers give and have highlighted some of our recent projects and the impact they have made. Don’t just take our word for it — read it for yourself.
In our customers’ wordsOur Customers
The partnership
behind the outcome
Atlas Thread Digital has the knowledge and experience to tackle even the most complex technical issues. Their ability to think outside the box to develop and tailor a solution that not only meets our current needs, but will grow with our laboratory, is something many other people and companies weren’t able to accomplish.
The ability to communicate the technical fixes to non-technical people is what really stands out — it made us feel like we were part of the solution.
Elevation Diagnostics
Automated Reporting, 20+ Hours a Week Recovered
Environmental laboratoryColoradoCustom application
Elevation Labs, an environmental testing laboratory in Colorado, was losing 20+ hours a week building specialized electronic data deliverables (EDDs) by hand. Their LIMS could only export through rigid Crystal Reports, and three outside coders, vendor support, and Excel macros had all come up short.
Atlas Thread Digital built a custom application that connects directly to the lab’s data, formats each deliverable automatically, and adds an upload path for information the LIMS could not capture. Hands-on reporting time dropped from 20+ hours a week to under one.
20+ → <1
hours / week
Hands-on reporting time reduced from 20+ hours a week to under one.
19+
hours recovered
Time returned to the laboratory team every week.
300–350
reports / month
Specialized reports now produced automatically.
~14
QA issues resolved
Distinct calculation and formatting issues resolved during QA.
Atlas Thread Digital · Proprietary Build
Production multi-agent AI platform on AWS
We built and operate our own agentic AI platform on AWS — three live business applications for support, CRM, and a pricing catalog sharing one secure data backbone, with a fleet of AI agents running in production. The agents draft and recommend; a human always decides. None can send an email, close a ticket, or change a price on its own.
Underneath sits the part most AI demos skip: a compliance layer with four-tier data classification, access enforced at read time, fail-closed PII redaction, and a tamper-proof audit trail exported to an isolated account. It is the same architecture we bring to regulated clients — proof that we run in production what we propose.
Production AI agents — three reasoning agents (support triage, customer outreach, and catalog health) plus a monitoring fleet, all suggest-only with a human in the loop
Retrieval-grounded on a PostgreSQL + pgvector backbone, so agents reason over real data, not guesses
AWS-native: ECS Fargate, Amazon Bedrock, RDS, a multi-account AWS Organization, Terraform, and single sign-on
Security and compliance plane: Public, Internal, Confidential, and Regulated data classes; clearance-checked reads; PII redaction that fails closed; and write-once audit logging to a locked, separate account
One shared library mediates every data access — so classification, redaction, and audit are automatic, not optional