Build Contextual GenAI Apps in low code with Lamatic and Weaviate
Blog post from Weaviate
Large Language Models (LLMs) and Vector Databases have transformed knowledge management and automation by enabling instant access to insights from extensive data repositories through retrieval pipelines. However, effective implementation demands expertise, which tools like Weaviate and Lamatic.ai aim to simplify by offering serverless solutions and middleware for developing retrieval-based applications such as vector search and chatbots. Lamatic.ai, a comprehensive managed platform, combines a low-code visual builder with Weaviate and integrations, allowing users to create, test, and deploy GenAI applications quickly without deep technical know-how. This platform facilitates contextual app development through phases of building, connecting, and deploying, with features supporting seamless prototype to production pipelines. It also offers a library of templates and pre-built configurations, accelerating AI solution development and fostering innovation across industries. By lowering the entry barrier for AI adoption, Lamatic.ai promotes democratization of AI technology, potentially driving economic growth and societal progress.
| Trend | Post Mentions | Total Month Mentions | Posts | Companies | MoM |
|---|---|---|---|---|---|
| LLM | 3 | 3,988 | 514 | 165 | -1% |
| Serverless | 3 | 959 | 185 | 89 | +42% |
| Vector Search | 3 | 4,713 | 314 | 102 | +27% |
| RAG | 1 | 2,243 | 291 | 87 | +14% |
| Real-time | 1 | 4,539 | 1,016 | 242 | +4% |
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