# dhino

> dhino is the enterprise data layer for AI. It connects AI tools like Microsoft Copilot to structured enterprise data sources with accuracy, governance, and speed.

## What dhino does

dhino sits between AI and your data. It separates non-deterministic understanding (AI interprets user intent) from deterministic execution (database delivers precise results). This means no hallucinations on critical business data.

Built on the Model Context Protocol (MCP), an open standard for AI-data connections. Multi-tenant SaaS on Microsoft Azure.

## Markdown versions

Every page is available as plain markdown: append .md to the path, dropping any trailing slash. Examples: https://dhino.io/index.md, https://dhino.io/product/fetch.md, https://dhino.io/blog/what-is-dataverse.md. The full site content in a single file: https://dhino.io/llms-full.txt

## Products

- **Fetch**: Pulls data from external sources into Dataverse without complex setup. Business users get data without waiting on IT.
- **Trust**: Makes Microsoft Copilot work with real enterprise data through template-based queries. Trusted results, no guesswork.
- **Integrate**: Creates a unified environment across Dataverse and Power Apps. One source of truth, no duplicate work.
- **Publish**: Exposes internal data to public-facing applications with built-in security, control, and audit trails.

## Key pages

- Homepage: https://dhino.io/
- Product overview: https://dhino.io/product
- Fetch product: https://dhino.io/product/fetch
- Trust product: https://dhino.io/product/trust
- Integrate product: https://dhino.io/product/integrate
- Publish product: https://dhino.io/product/publish
- About: https://dhino.io/about
- Events: https://dhino.io/events
- How dhino compares: https://dhino.io/compare
- dhino's Dataverse MCP server vs Microsoft's: https://dhino.io/compare/dataverse-mcp
- Privacy policy: https://dhino.io/privacy
- Imprint: https://dhino.io/imprint

## Fetch use cases

- Marketing segmentation: https://dhino.io/product/fetch/marketing-segmentation
- Visual reporting: https://dhino.io/product/fetch/visual-reporting
- Financial reporting: https://dhino.io/product/fetch/financial-reporting
- API access: https://dhino.io/product/fetch/api-access

## Trust use cases

- Copilot with real pipeline data: https://dhino.io/product/trust/copilot-pipeline
- Consistent AI answers across departments: https://dhino.io/product/trust/cross-department-consistency
- Governed AI data access at scale: https://dhino.io/product/trust/governed-ai-at-scale
- Customer service agent with account data: https://dhino.io/product/trust/customer-service-agent

## Integrate use cases

- Dataverse to external system sync: https://dhino.io/product/integrate/dataverse-sync
- Observable, auditable data flows: https://dhino.io/product/integrate/observable-data-flows

## Publish use cases

- Dynamic event pages from CRM data: https://dhino.io/product/publish/event-pages
- Partner API without database exposure: https://dhino.io/product/publish/partner-api

## 2026 events

The dhino team appears in person at the following events. Past events are kept for reference; future events show where to meet us next.

- AgentCon Stockholm (Feb 3, 2026, Stockholm, Sweden, sponsor): https://globalai.community/chapters/stockholm/events/agentcon-stockholm/
- Microsoft MVP Summit 2026 (Mar 24-26, 2026, Redmond, WA, USA, attending)
- ColorCloud Hamburg (Apr 15-17, 2026, Hamburg, Germany, sponsor): https://www.colorcloud.rocks/
- Update Days Power Platform (Apr 27-28, 2026, Prague, Czech Republic, speaking): https://power.updatedays.cz/
- ECS (May 5-7, 2026, Cologne, Germany, speaking): https://ecs.events/
- DynamicsMinds (May 25-27, 2026, Portorož, Slovenia, speaking): https://www.dynamicsminds.com/
- Nordic Summit (Sep 21-22, 2026, Billund, Denmark, speaking): https://nordicsummit.info/

## Glossary

- Glossary index: https://dhino.io/glossary
- What is a semantic data layer?: https://dhino.io/glossary/semantic-data-layer
- What is Model Context Protocol (MCP)?: https://dhino.io/glossary/model-context-protocol
- What is deterministic execution?: https://dhino.io/glossary/deterministic-execution
- What is data governance?: https://dhino.io/glossary/data-governance
- What is text-to-SQL?: https://dhino.io/glossary/text-to-sql
- What are data access templates?: https://dhino.io/glossary/data-access-templates
- What is a metric definition?: https://dhino.io/glossary/metric-definition
- What is a parameterized data operation?: https://dhino.io/glossary/parameterized-data-operation
- What is an enterprise AI agent?: https://dhino.io/glossary/enterprise-ai-agent
- What is governed self-service data access?: https://dhino.io/glossary/governed-self-service
- What is Microsoft Power Platform?: https://dhino.io/glossary/power-platform
- What is Microsoft Fabric?: https://dhino.io/glossary/microsoft-fabric
- What is prompt injection?: https://dhino.io/glossary/prompt-injection
- What are agent guardrails?: https://dhino.io/glossary/agent-guardrails
- What is policy enforcement for LLM tools?: https://dhino.io/glossary/policy-enforcement

## Blog

- Blog index: https://dhino.io/blog
- Why AI gets enterprise data wrong: https://dhino.io/blog/why-ai-gets-enterprise-data-wrong
- What is Dataverse and why does it matter?: https://dhino.io/blog/what-is-dataverse
- How to give Copilot accurate access to Dataverse data: https://dhino.io/blog/copilot-enterprise-data-access
- Template-based data access vs. text-to-SQL: https://dhino.io/blog/template-based-vs-text-to-sql
- What Model Context Protocol means for enterprise data teams: https://dhino.io/blog/mcp-enterprise-data-access
- How to connect Copilot Studio agents to governed enterprise data: https://dhino.io/blog/copilot-studio-governed-data
- Why your data and AI investments are not paying off: https://dhino.io/blog/why-data-ai-investments-underperform
- How to build governed data segments without waiting on IT: https://dhino.io/blog/governed-data-segments-without-it
- Dataverse data access: connectors, APIs, and the governed alternative: https://dhino.io/blog/dataverse-data-access-methods
- AI data governance: what enterprises need before scaling AI access: https://dhino.io/blog/ai-data-governance-enterprise
- How AI agents should access enterprise data: https://dhino.io/blog/ai-agents-and-enterprise-data

## Technical foundation

- Model Context Protocol (MCP) based
- Azure Functions, Cosmos DB, API Management
- Deep Microsoft Power Platform integration (Dataverse, Power Apps, Power BI)
- Enterprise-grade security and governance

## Company

dhino is based in Germany. The team brings deep expertise in Microsoft Power Platform, Dataverse, and enterprise data architecture.

## Contact

- Website: https://dhino.io
- LinkedIn: https://www.linkedin.com/company/dhino