Workflow Layer Enables Model Swapping

This reveals that the real product is not the model, it is the operating layer that sits between a biotech’s documents and the model of the month. In practice, that layer stores who can access which repositories, which template matches a tech transfer packet or Module 3 section, which checks a draft must pass, and which reviewer gets the next task. If the model changes, the company keeps the same permissions, templates, tools, review routes, and acceptance tests, so the workflow survives even as the reasoning engine underneath changes.

• Raycaster is building on top of systems of record like Veeva, IQVIA, SharePoint, and LIMS, not replacing them. The sticky asset is the company specific map of objects, rules, and review logic that turns messy document work into repeatable steps with page linked evidence.
  1 sacra 2 sacra
• This is the same direction the category is taking elsewhere. Harvey moved from generic legal chat toward packaged workflows and guardrails, and Hebbia built a control surface for non technical users to run multi step retrieval workflows. The common pattern is workflow scaffolding first, model choice second.
  1 sacra 5 sacra
• Large incumbents are also becoming model flexible. Veeva says its AI is LLM agnostic and can use either Veeva supplied or customer specific models, while keeping workflows, permissions, and audit trails inside Vault. That makes workflow ownership, not raw model access, the key control point in life sciences AI.
  3 veeva 4 veeva

The market is heading toward a split where foundation models keep improving general reasoning, while vertical vendors own the context, tests, and action paths that make AI usable inside regulated work. As incumbents add model agnostic agents into their core systems, the winners will be the companies whose workflow layer becomes the default way regulated teams draft, review, and approve work.