AIthena

AIthena is the data layer of the stack. Navari's agents are only as good as the data they can reach, and an Agentis use case stalls without it. Most of what I know about enterprise AI I learned here: the model was never the bottleneck. The data supply chain was.

The problem

A trial generates data every week, and most of it sat in study-specific, vendor-specific shapes until someone curated it by hand, usually months after the fact. Dozens of hand-offs stood between a dataset and a model that could use it. Everyone was working on the end of the pipeline, AI consumption, while the beginning, how data gets generated and contracted, stayed as it was.

What AIthena is

An operating model that treats clinical and translational data as a regulated product. There's no new tool to install.

• A data pod per study, with a named owner accountable for the data's release and quality.
• Release gates from study design through close, so standards are set in the biomarker plan and the vendor contract instead of patched on later.
• Vendor data delivered to specification, with acceptance criteria that have teeth.
• FAIR at source: findable in a catalog, accessible through APIs, interoperable through common data models, reusable with lineage.

The proof point

The first deliverable was a ctDNA atlas: circulating tumor DNA linked to clinical data across 24 trials and 4 vendors, harmonized, self-serve, AI-ready. Concept to MVP took two months. It needed the company's first internal data agreement of its kind to open the data across the R&D organization, and time to analysis for that data dropped from weeks to days, roughly 10x. The same model then went onto cell therapy programs and into automated curation.

My part

I conceptualized the program, structured its workstreams, secured the sponsorship and sat on its steering committee. A program lead ran it end to end and owns the delivery. When I handed off in mid-2026, AIthena was moving from pilot to enterprise scale. I haven't tracked it since.

Where it fits

Agentis decides which questions get an agent. AIthena gets the data ready. Navari builds and runs the agent. Of the three, this is the one that outlives any particular model.