FlowiseAI (YC S23)

FlowiseAI (YC S23)

Software Development

San Francisco, California 5,224 followers

Low-code LLM apps builder

About us

Flowise is an open source drag & drop tool to build your customized LLM flow. We provide a visual interface to let you build backends for LLM apps used for QnA, summarization and analysis on your documents.

Industry
Software Development
Company size
2-10 employees
Headquarters
San Francisco, California
Type
Privately Held

Locations

Employees at FlowiseAI (YC S23)

Updates

  • Flowise v2.1.4 release 🥳 📈 Prometheus Grafana, OpenTelemetry Native support for Prometheus with Grafana and OpenTelemetry for metrics such as API requests, counts of flows/predictions. https://lnkd.in/eYb8v5bM 🦙 Ollama multi modal Process images, files and enable JSON mode ✨ Cerebras LLM Use Cerebras Systems lightning fast inference speed that can delivers 1,800 tokens/sec for Llama 3.1-8B and 450 tokens/sec for Llama 3.1-70B, 20x faster than NVIDIA GPU-based hyperscale clouds. 🛋️ Couchbase Vector Store Couchbase is the NoSQL cloud database platform for business-critical, AI-ready applications. Leverage their vector search capabilities for RAG apps ✍ Override Configuration ⚠️ BREAKING Change Due to security reason, override config is disabled by default. User must explicitly enable this in the Security tab. https://lnkd.in/eE6ATVfy 🗄️ Postgres, MySQL support for Agent Memory Agent Memory is a crucial piece when designing an agentflow. It remembers the state, checkpoints of the conversation. Now supporting PostgresQL and MySQL! 🌐 Global Proxy If you're running Flowise in an environment that requires a proxy, such as within an organizational network, you can configure Flowise to route all its backend requests through a proxy of your choice. https://lnkd.in/ei7U7mzm There are still lots of bugfixes and improvements contributed by community 🙌 For more details, take a look at the release: https://lnkd.in/eHFGfWqj

    • No alternative text description for this image
    • No alternative text description for this image
    • No alternative text description for this image
    • No alternative text description for this image
    • No alternative text description for this image
  • This is definitely an interesting use case of LLM!

    View profile for Mohamed Yasser, graphic

    Government Solution Architect | Emerging Technology Strategist | Technology Analyst | Visionary Futurist | Community Builder | Mentor for Future Tech Leaders

    Introducing an Automated Architecture Diagram Generator I’ve recently developed a tool leveraging Groq, FlowiseAI (YC S23), Qdrant, and Mistral AI Embed to streamline the process of creating architecture diagrams from simple descriptions. Built with Streamlit for accessibility, this tool enables efficient translation of architecture statements into visual diagrams without manual intervention. It was built in 2 hours Key Technologies: FlowiseAI (YC S23): Manages flow and data transformations effectively. Qdrant: Ensures fast, high-quality vector similarity search. Mistral AI Embed: Delivers accurate embeddings, enhancing model understanding. Groq: Optimizes the computational power for intensive LLM tasks. The process is straightforward: 1. Users input an architecture statement. 2. The system interprets this using advanced embeddings. 3. The generated Python code is executed to produce a clean, professional architecture diagram. For teams and developers, this tool significantly reduces diagram creation time while maintaining clarity and precision. If you're interested in automating your architecture design process or would like to discuss ideas for further improvement, let’s connect. Demo:https://lnkd.in/dM5SnD5M #AI #MachineLearning #Flowise #Qdrant #Groq #MistralEmbed #Automation #ArchitectureDesign #Streamlit

    • No alternative text description for this image
  • Flowise v2.1.3 is now out and comes with a lot of goodies 🎃 📂 Full and RAG File Uploads - RAG file uploads embed and upsert to the vector store in real-time. - Full file uploads send entire files to the LLM, ideal for large-context models like Gemini and Claude. See how we upload a CSV and generate a summary graph using the full file upload feature 👇 🔥 New LLMs and Embeddings - Claude 3.5 Sonnet from Anthropic, Bedrock, Vertex - NVDIA Nemo Guardrails - JinaAI Embedding - Alibaba Tongyi - Cerebras Thank you to all the contributors! As always lots of bugfix and small improvement: https://lnkd.in/eJJatgHm

  • We released a small update v2.1.2 but its immensely useful 🌐 OpenAPI Toolkit This allows you to upload an OpenAPI 3.0 YAML spec file, and automatically convert each APIs into set of tools for function calling. From the demo video, we uploaded OpenAI API yaml file with 20 endpoints and have the LLM automatically picks and executes the tools required to answer user query. 💬 Follow up questions Generate follow up questions based on the previous conversation All this and more, including tons of bug fixes and UI/UX improvements, in the latest v2.1.2! https://lnkd.in/dsph3WMU

  • FlowiseAI (YC S23) reposted this

    View profile for Mahmoud El Orfali, graphic

    Data Analytics and AI Expert - CGB

    <<< An example of #Healthcare #Innovation Using #Generative #AI >>> With the recent code interpreter and file upload features from E2B, and FlowiseAI (YC S23), I built a #Diabetes #AI Advisor and Assistant equipped with #Data #Analytics Tools to aid patients, parents, and doctors in smartly monitoring, managing, and gaining more insights from diabetes data records. The uploaded data are upserted to its own #vector store, alongside its time-series data. This allows for comparisons to be made over longer time periods.  #HealthTech #MedicalAI #ArtificialIntelligence 

Similar pages

Funding

FlowiseAI (YC S23) 1 total round

Last Round

Pre seed

US$ 500.0K

Investors

Y Combinator
See more info on crunchbase