Eliminate the AI-Pilot-to-Production Gap
LazyFox gives AI a shared understanding of your business.
Works with your existing stack. Live in days. No migration required.
Customer story
We bring together the LazyFox platform and hands-on deployment work to build solutions around the problem your business actually has. At Finway, that meant one governed definition behind every report, live in hours.
Spend management · MunichLazyFox replaced hard-coded MongoDB queries with a single governed layer, provisioned centrally for every Finway customer inside its own product.
“LazyFox enables best of both worlds where you’re getting the AI capability of query building, but the deterministic capabilities of having an actual database query that you can rely on every time.”
Alex PalaioroutasHead of Product, finwayLazyFox Enterprise AI Adoption Platform
The Payoff
Governs what every metric means across your stack, so every AI tool, agent, and report returns the same governed answer: deterministic, versioned, role-aware, with an audit trail your CFO signs and your regulator accepts.
Learn about trusted answers →Every resolved conflict and approved definition becomes governed precedent: a knowledge graph of what your business means that compounds inside your company, not inside your model vendor.
Learn about staying vendor-agnostic →Connects read-only to your existing systems and builds a governed semantic layer from what's already there.
Learn about the data catalog →Monitors every connected source for conflicts and drift before your AI inherits them, versioning every approved definition automatically.
Learn about the data catalog →Enables your domain experts in natural language, eliminating the IT-Business coordination bottleneck on every update.
Learn about natural language analytics →Governs the context layer beneath Claude, Gemini, Slack AI, making each one more accurate without a rollout or a change of tools.
Learn about integrations →
Claude
Gemini
Slack AI
SAP
Salesforce
MongoDB
DatabricksDefinitions are built once at setup; every governed query then runs directly from code with zero per-query model calls. Routine token spend drops 60-80%, so the layer funds itself.
Learn how to cut your token bill →Computer use lets agents operate SAP and other legacy systems through the screen, without an API project. Access stops being the constraint, and the definitions nobody wrote down become an operational risk.
Read → ResearchModels did not get better at storing financial state. They got better at the work that happens before anything reaches a ledger, and that work spans every other system you run.
Read → ResearchTwo different problems: a process nobody redesigned, then an enterprise whose systems cannot agree what its own numbers mean. What each looks like, and what to do about them.
Read →LazyFox is an enterprise AI adoption platform that reconciles what data means across every system a business runs, so AI tools return the same, correct answer every time. It sits read-only on top of the stack a company already has (Databricks, Salesforce, SAP, Snowflake, MongoDB, and more), rather than requiring a migration to a new platform.
Enterprises use LazyFox to remove three barriers to reliable AI: reaching data that's locked away, resolving conflicting metric definitions, and producing answers that can be explained and audited. It goes live in days, with no data shared with the underlying AI models.