validating.si
Every output, validated.
About the name
What validating.si means
Validating is the work a regulated company must do before it trusts a model, and keep doing after launch. Banks call it model risk management. Drug and device makers call it software validation. Both rulebooks changed in the past year. In September 2025 the FDA finalised its Computer Software Assurance guidance, a risk-based way to validate production and quality-system software. In April 2026 the Federal Reserve issued SR 26-2, replacing the 2011 model risk guidance known as SR 11-7. A Databricks analysis notes that generative and agentic AI sit formally outside its scope while inheriting its principles. That gap is a product category. validating.si names the team, tool or service that tests a model against its intended use, records the evidence and repeats the check whenever the model, data or prompt changes.
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A workbench for bank validators
Model validators in large banks still assemble evidence by hand in documents and spreadsheets. A workbench that runs challenger models, tracks drift and drafts the validation report in the structure supervisors expect turns a quarterly scramble into a living file. Sell per model inventory to institutions above $30 billion in assets, where the Fed says SR 26-2 is most relevant.
GxP sign-off for AI features
Pharma quality teams want AI for deviation reports and batch record review, but every tool must be shown fit for its intended use. A service that maps each AI feature to process risk, scripts the assurance testing and packages objective evidence in line with the FDA's risk-based approach gets AI past the quality unit. Buyers: manufacturers, CDMOs, testing labs.
Inline checks on every response
Production LLM apps fail quietly: a malformed field, a figure outside policy, a missing disclosure. An inline layer that validates each response against schemas and business rules, retries or blocks failures, and logs every verdict gives engineers uptime and gives compliance a record. Price per million checked responses.
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Questions
About validating.si
Why validating and not validation?
Validation is a document you finish. Validating is a process that never stops, which is how both rulebooks now frame the duty: risk-based, ongoing, tied to each change. The -ing form sells that stance. It also reads naturally inside a product, where the name describes what the software is doing at that moment: validating this release, this prompt, this model.
Is validating.si only for banks and pharma?
Those buyers have the deepest pockets because the duty is written into supervisory guidance. Any team shipping model outputs into production has the same need at smaller scale: insurers, lenders, healthcare software, public services. The name works for a horizontal developer tool and a specialist consultancy alike, because both sell one outcome: proof that the system does what it claims.
What evidence should a validating product export?
The record an inspector asks for: intended use, the risk assessment that set the depth of testing, test results, known limits and monitoring after release. The FDA's guidance expects objective evidence across the software lifecycle. Build that export once per regulatory format and your product stops being a test tool and becomes the system of record.
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