# zaimler > zaimler gives AI agents a live, governed understanding of your business, built from the data you already have and resolved at runtime. > The list below indexes the publicly accessible pages of this site for AI systems and LLM agents. Full Markdown content of every page is available at https://www.zaimler.ai/llms-full.txt ## Public Resources - [Home](https://www.zaimler.ai/): zaimler gives AI agents a live, governed understanding of your business, built from the data you already have and resolved at runtime. - [About](https://www.zaimler.ai/about): Who zaimler is, the team, and the mission behind the product. - [Careers](https://www.zaimler.ai/careers): Open roles and what it is like to work at zaimler. - [Security](https://www.zaimler.ai/security): How zaimler keeps your business context secure — architecture, data handling, and compliance. - [Press Kit](https://www.zaimler.ai/press-kit): Boilerplate, brand assets, founder bios, and imagery for press coverage of zaimler. - [Contact](https://www.zaimler.ai/contact): Get in touch with zaimler and book a demo. ## Products - [Explorer](https://www.zaimler.ai/product/explorer): Ask in plain language instead of writing SQL, and get the answer with its reasoning path: which entities, which relationships, which source rows it came from. - [Governance](https://www.zaimler.ai/product/governance): Tag the data that matters, set access policy once, and run every agent call through it. Role and attribute rules enforced per request, with an audit log. - [Ontology](https://www.zaimler.ai/product/ontology): zaimler infers a unified domain model across your sources, with confidence scores, and your own engineers confirm it. A working model in days, not quarters. - [Platform](https://www.zaimler.ai/product/platform): Federate Snowflake, Databricks, BigQuery and more where they already live. No migration, no copies, and every answer resolves with the path behind it. ## Solutions - [Asset Management](https://www.zaimler.ai/solutions/by-industries/asset-management): See real exposure across every mandate from one live understanding of the business. Positions, counterparties and limits resolved at the moment you ask. - [Banking](https://www.zaimler.ai/solutions/by-industries/banking): Flag fraud and clear model risk management review from a live understanding of your business, kept inside your walls. Every answer traceable to its source row. - [Healthcare](https://www.zaimler.ai/solutions/by-industries/healthcare): Check claims against a live understanding of your business so payment integrity holds. Every determination traceable to policy, member and source record. - [Insurance](https://www.zaimler.ai/solutions/by-industries/insurance): Put AI on claims, fraud and underwriting with a live understanding of your policies. Every decision traceable to source for an adjuster or a regulator. - [Telecommunications](https://www.zaimler.ai/solutions/by-industries/telecommunications): Answer subscriber and network questions from a live understanding of the business, and defend each one in a revenue assurance review with the path behind it. - [Agents](https://www.zaimler.ai/solutions/by-use-case/agents): Agents stall before production because they guess. Ground every agent in a live understanding of your business and run each call it makes through your policies. - [Data](https://www.zaimler.ai/solutions/by-use-case/data): Ask in plain language instead of writing SQL, and get an answer resolved against current data the same way every time, with the source rows behind it. - [Data Sovereignty](https://www.zaimler.ai/solutions/by-use-case/data-sovereignty): Data sovereignty in practice: zaimler deploys inside your own private VPC, so your data and your models never leave it. You choose every model that runs. - [Token Optimization](https://www.zaimler.ai/solutions/by-use-case/token-optimization): Route the high-volume work to smaller models and let resolved context carry them. The same answers, at a fraction of what frontier models cost to run. ## Blog - [Field notes on context for enterprise AI](https://www.zaimler.ai/blog): zaimler provides the runtime context layer between enterprise data and enterprise AI. Dive in to learn how accuracy beats similarity, and how agents survive production. - [When Semantic Embeddings Break: Why No Cosine Threshold Will Save You](https://www.zaimler.ai/blog/when-semantic-embeddings-break): A cosine score ranks related terms. It cannot decide which ones are the same. - [Five reasons data catalogs can't be a context layer](https://www.zaimler.ai/blog/data-catalog-vs-context-layer): Data catalogs were built for design-time discovery & governance. AI agents need runtime context. Five structural reasons the catalog rebrand won't hold. - [Two Summits, Same Blueprint](https://www.zaimler.ai/blog/context-layer-five-mechanisms): What Snowflake and Databricks announced in June 2026, and the five mechanisms behind any "context layer" claim - [Inverting the semantic layer](https://www.zaimler.ai/blog/inverting-the-semantic-layer): Every stack already has a semantic layer that describes data and leaves meaning to be guessed at per query; inverting it changes what's answerable. - [Your best questions aren't retrieval questions](https://www.zaimler.ai/blog/structural-questions): Retrieval assumes the answer is sitting somewhere, waiting to be found. For the questions enterprises most want answered, it isn't. - [Most "Ontologies" Don't Reason. Build Yours in the Right Order Anyway.](https://www.zaimler.ai/blog/ontology-maturity-ladder): An opinionated maturity path for ontology-like structures in the agentic era - [Metric status is a trust signal, not paperwork.](https://www.zaimler.ai/blog/metric-status-trust-signal): What draft, published, and certified have to mean now that agents read the catalog too, and why the labels you already have are quietly running your board deck. - [Context Layer: Feature or Platform?](https://www.zaimler.ai/blog/context-layer-feature-or-platform): What talking to your data actually requires, and ten questions that follow from it ## Policies - [Privacy Policy](https://www.zaimler.ai/privacy-policy): How zaimler collects, uses, and protects personal data. - [Terms of Service](https://www.zaimler.ai/terms-of-service): The legal terms governing use of zaimler.