Docs - Community - Why Morphik Core? - Bug reports
## Morphik Core is a AI-native toolset for visually rich documents and multimodal data We are building the best way for developers to integrate context (however complex and nuanced) into their AI applications. We offer a treasure chest of tools to store, represent, and search (shallow, and deep) unstructured data. End-to-End. ## Why? Building AI applications that interact with data shouldn't require duct-taping together a dozen different tools just to get relevant results to your LLM. Traditional RAG approaches that work in proof-of-concepts often fail spectacularly in production. Cobbling together separate systems for text extraction, OCR, embeddings, vector databases, and retrieval creates fragile pipelines that break under real-world load. Each component brings its own APIs, configurations, and failure modes - what starts as a simple demo becomes an unmaintainable mess at scale. Even worse, these pipelines fundamentally fail at understanding visually rich documents. Charts become meaningless text fragments. Critical diagrams lose their spatial relationships. Tables get mangled into unreadable strings. Technical specifications with mixed text and visuals? Forget about accuracy. The result is AI applications that confidently return wrong answers because they never truly understood the documents. They miss crucial information embedded in images, misinterpret technical diagrams, and treat visual data as an afterthought. And performance? Watch your infrastructure costs explode as your LLM re-processes the same 500-page manual for every single query. ## What? [Morphik Core](https://dev.morphik.ai) provides developers the tools to ingest, search (deep and shallow), transform, and manage unstructured and multimodal documents. Some of our features include: - [Multimodal Search](https://dev.morphik.ai/docs/concepts/colpali): We employ techniques such as ColPali to build search that actually *understands* the visual content of documents you provide. Search over images, PDFs, videos, and more with a single endpoint. - [Fast and Scalable Metadata Extraction](https://morphik.ai/docs/concepts/rules-processing): Extract metadata from documents - including bounding boxes, labeling, classification, and more. - [Integrations](https://morphik.ai/docs/integrations): Integrate with existing tools and workflows. Including (but not limited to) Google Suite, Slack, and Confluence. The best part? Morphik Core has a [free tier](https://dev.morphik.ai/pricing)! Get started by signing up at [dev.morphik.ai](https://dev.morphik.ai/signup). ## Table of Contents - [Getting Started with Morphik Core](#getting-started-with-morphik-core-recommended) - [Self-hosting Morphik Core](#self-hosting-morphik-core) - [Using Morphik Core](#using-morphik-core) - [Contributing](#contributing) - [Open source vs paid](#License) ## Getting Started with Morphik Core (Recommended) The fastest and easiest way to get started with Morphik Core is by signing up for free at [dev.morphik.ai](https://dev.morphik.ai/signup). We have a generous free tier and transparent, compute-usage based pricing if you're looking to ingest a lot of data. ## Self-hosting Morphik Core If you'd like to self-host Morphik Core, you can find the dedicated instruction [here](https://dev.morphik.ai/docs/getting-started). We offer options for direct installation and installation via docker. **Important**: Due to limited resources, we cannot provide full support for self-hosted deployments. We have an installation guide, and a [Discord community](https://discord.gg/BwMtv3Zaju) to help, but we can't guarantee full support. ## Using Morphik Core Once you've signed up for Morphik Core, you can get started with ingesting and searching your data right away. ### Code (Example: Python SDK) For programmers, we offer a [Python SDK](https://dev.morphik.ai/docs/python-sdk/morphik) and a [REST API](https://morphik.ai/docs/api-reference/health-check). Ingesting a file is as simple as: ```python from morphik import Morphik morphik = Morphik("