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Schema Sense: AI-native tooling that creates trusted data pipelines at unmatched speed




Today, we’re introducing Schema Sense: Federato’s approach for faster, more transparent data onboarding. This capability has been shown to map up to 84% of customers’ native data schemas to our full lifecycle platform’s signature federated graph, cutting months off implementation timelines. Now, we’re making this AI-native tooling set the de facto standard for accelerating implementations across all of our customers.
Schema Sense replaces the guesswork and brittle plumbing that insurers have historically used to integrate into legacy enterprise systems. By making each connection explicit and intelligible, and allowing AI to do the heavy lifting so corners don’t get cut, and teams gain the speed, transparency, and control they need to validate inputs and trust that the platform will behave predictably as their business evolves.
Schema Sense uses AI to accurately map up to 84% of your native data automatically—cutting months off implementation and delivering cleaner, more reliable data from day one.
The industry has reached a breaking point with the Old Core’s traditional implementation models. Hundreds of millions in spend. Years of work with little to show for it. Finger-pointing and job loss. Every insurer has felt the pain of endless back-and-forth. When integrations start on shaky ground with limited visibility, everything downstream—risk selection, underwriting workflows, pricing logic, portfolio insights—becomes slower and harder than it needs to be.
Schema Sense’s innovative approach to data mapping solves this by giving teams what Old Core systems never have: a shared, transparent, AI-assisted model of how your information moves through and powers the full policy lifecycle. With clarity in place, every workflow becomes easier to build, faster to adapt, and far more reliable over time.
Schema Sense collapses weeks of back-and-forth into an unambiguous, predictable set of steps, eliminating the endless clarification loops that drag down most onboarding cycles. Teams align faster, make fewer assumptions, and move through milestones in a fraction of the time.
Results from our beta testing group suggest this can save customers more than 100 hours of work, cutting out months of effort. That time savings translates directly into faster go-lives and the ability to bring new programs online sooner.
Every transformation is explicitly surfaced. No black boxes. No “engine magic.” Just intelligible, auditable logic demonstrating how data flows into Federato. For the first time, insurers gain full data provenance: a clear lineage of where each value originated, how it changed, and where it ultimately lands. This makes debugging easier, audits faster, and downstream workflows far more reliable.
For organizations accustomed to decades-old, opaque pipelines born from legacy systems, this level of visibility alone is transformative. Customer teams and Federato’s forward deployed engineers partner with AI and each other to follow standardized processes that prevent corner-cutting and save massive headaches when systems inevitably drift and change.
When data is mapped transparently and consistently from day one, the platform behaves predictably as your business evolves. Workflows remain consistent. Insights remain trustworthy. And data and product updates become easier instead of riskier. With version tracking layered in, every change becomes auditable and reversible, strengthening governance and giving teams more control as they iterate faster across workflows.
Schema Sense brings together automation, transparency, and collaboration to make onboarding straightforward and predictable.
Ultimately, it’s designed for insurers who want to move faster without sacrificing control.
Schema Sense marks a shift in how insurers prepare, align, and activate information across the Federato platform. By replacing fragmented, opaque data plumbing with an AI-native onboarding experience, insurers finally get what’s been missing: a clean, adaptable, future-ready starting point for every workflow they build.
