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    Strategic partner · Database and AI

    MongoDB with Semantix: flexible data for modern applications and AI agents

    Semantix modernizes applications and databases with MongoDB, migrates data from legacy databases and prepares the foundation for vector search and AI agents. Operations continue with ongoing support and evolution.

    Find where to start →

    What Semantix does with MongoDB

    • Data modernization

      We migrate data from relational and legacy databases to a more flexible model, without stopping the application.

      Also known as: Data Modernization

    • Modern applications

      Applications rewritten or evolved on a foundation that keeps pace with business change.

      Also known as: Application modernization

    • Foundation for AI

      Vector and semantic search so agents find the right information in company data.

      Also known as: MongoDB Atlas · Vector Search

    • Operations and support

      Performance, availability and cost monitored by a dedicated team.

      Also known as: Managed Data Services

    • Data strategy

      An assessment of your databases and a prioritized plan to modernize what weighs most.

      Also known as: Data Journey Strategy Consulting

    • Data platform

      Architecture, pipelines and support for the database, with security and backups.

      Also known as: Data Platform Foundation · Data Factory · data platform AMS

    With the Semantix AI Suite

    LinkAPI connects Semantix AI Suite agents to MongoDB databases, with access only to what each agent needs. Modernix helps move legacy systems to modern architectures, and Safetix logs every action.

    Explore the Semantix AI Suite →

    Use cases

    Application examples

    • Catalog and master dataProducts, customers and contracts with different formats live in the same database.
    • A modernized legacy systemAn old application gets a current database, migrated in stages.
    • Search for agentsAgents find documents and records by meaning, not just by exact words.

    Frequently asked questions

    Common questions

    When does MongoDB make sense?

    When data changes format often, when the application needs to scale quickly or when AI agents need to search for information by meaning.

    Does Semantix migrate data from relational databases to MongoDB?

    Yes. We plan the new data model, migrate in stages and keep the application running during the transition.

    Can MongoDB serve as a foundation for AI agents?

    Yes. Vector search lets agents find information by meaning. LinkAPI connects agents to the database with permissions.

    Start with the process, not the technology

    An assessment shows where value is stuck in your operation and which technology, the one you already have or the best fit, solves it first.

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    Technology from the Semantix partner ecosystem. Names and trademarks belong to their respective owners.

    Not sure what a term means? That’s fine

    Nobody should have to speak technology to understand a transformation.

    Enterprise AI Company
    A company that brings AI into the operations of large enterprises: it delivers the platform, builds with the client’s team or runs the processes with AI agents and specialists.
    Hybrid workforce
    AI agents handle the volume; specialists decide the exceptions and the risky cases.
    Operation that learns
    Every human decision becomes knowledge, so the next similar case is faster and cheaper.
    Outcome-based contract
    You pay for what is delivered and measured, such as tickets resolved or cost per transaction.
    Context
    Your company’s knowledge (data, processes, rules and decisions) that lets AI act safely.
    AI
    Computers able to perform tasks that would normally require human intelligence.
    Agent
    An AI system that can carry out tasks using tools.
    Workflow
    The path a piece of work travels inside a company.
    API
    A way of letting systems talk to each other.
    Cloud
    Computing and storage reached over the internet.
    Data Platform
    An environment that organizes and serves the company’s data.
    Agentic AI
    AI that can understand goals and carry out tasks within defined limits.
    AI Harness
    The structure that supplies the context, tools, rules and controls an agent needs to act safely.