Customer Story
How Llaama built T2R2 on Akka — immutable audit trails and reproducible AI workflows for AI-driven treatment development, addressing the USD 7 billion lost each year to irreproducible clinical studies.
Llaama built T2R2 to give biopharma research teams reproducibility of both workflows and results. The system records every step of AI and data-science pipelines as an immutable audit trail and a directed acyclic graph across distributed containers and sites — the traceability biopharma needs to move research into approved treatments faster, and to recover the USD 7 billion lost each year to irreproducible clinical studies.
Akka ROI Scorecard
Akka delivered the audit-trail and streaming infrastructure that Llaama estimates would have taken months of DevOps and database administration to build in-house.
the annual industry loss from irreproducible clinical studies that T2R2's reproducible workflows are built to recover.
of workflow steps captured as an immutable audit trail and DAG, across every container and site in a distributed research pipeline.
Business outcome: reproducible workflows and results, with data lineage and enforceable data contracts between research partners.
Biopharma research runs across fragmented teams, distributed environments, and mixed AI and data-science tooling. That fragmentation breaks reproducibility and traceability: results are hard to reconstruct, lineage is lost between partners, and the path from a research finding to an approved drug or clinical practice stalls. The industry loses an estimated USD 7 billion each year in clinical studies that cannot be reliably reproduced.
Llaama set out to fix reproducibility at the infrastructure level. Doing that in-house meant building immutable audit trails, data-lineage tracking, and streaming coordination across containers and locations — months of DevOps and database administration before any research value appeared.
Llaama delivered T2R2 through Akka. Llaama required a reproducibility and traceability envelope over distributed AI workflows, plus the research data sources T2R2 governs. They received a production system that records every workflow step as an immutable audit trail and a directed acyclic graph, deduces workflow structure with AI, and enforces data contracts between partners. As CEO Bernard Deffarges put it, "What Akka gave us out-of-the-box would have taken months of DevOps and database administration to achieve ourselves." The streaming coordination underneath keeps distributed pipelines synchronized across containers and sites. Deffarges: "The streaming features within Akka make it really smooth, fast and responsive."
Chief Quality Officer, Suzanne Studinger: "Traceability is a crucial requirement in pharmaceutical development; biopharma companies need to know who did what, when, and why, even down to the level of the infrastructure. There are solutions that can reproduce a workflow, but with no guarantee that there's traceability or that the output is going to be always the same," says Studinger. "With Akka, T2R2 offers reproducibility of both workflows and results."
One of the biggest values of the solution is enabling compliance by design. This also contributes strongly to cutting the time to market for new drugs or clinical approaches. Being able to beat competitors to market can translate into huge profits.
"With Akka, we can focus on our business logic, while the infrastructure, the deployment, and everything else happens like magic!"
Scale. T2R2 captures every step of an AI or data-science workflow as an immutable audit trail and a directed acyclic graph, spanning all containers and sites in a distributed research pipeline. Data lineage is preserved end to end, and data contracts govern how research partners exchange results.
Cost to operate. Reproducible workflows target the USD 7 billion the industry loses each year to irreproducible clinical studies. Akka delivered the underlying infrastructure, enabling Llaama to minimize the DevOps and database-administration burden for the audit-trail and streaming layer.
Speed to production. Infrastructure that Llaama estimated at months of internal DevOps and database work arrived out-of-the-box, moving T2R2 to a working system in weeks.
Business impact. Biopharma teams get reproducibility of both workflows and results — the traceability required to translate research into approved treatments and clinical practice with confidence.
T2R2 already governs distributed AI workflows in a regulated field. The next step is agents that act inside that governed envelope: agents that mine research and trial data for lineage gaps, propose candidate treatments from prior results, and drive regulated pipelines from finding to submission — every action written to the same immutable audit trail T2R2 records today. That is the delivered-outcome path of Akka Specify. Llaama hands over specifications — the reproducibility rules, a regulated risk envelope, and the research knowledge sources the agents draw on — and Akka delivers and operates a governed production system in weeks, with Llaama carrying none of the operational load.
The platform that made T2R2 reproducible is the same platform that builds and runs agentic AI. Enterprises build on the Akka Agentic AI Platform directly, or have a governed system delivered and operated through Akka Specify. Both provide the traceability and production guarantees regulated biopharma work demands.
