An alternative to Text-to-SQL We launched pxt.retrieval_udf(), a feature that transforms any Pixeltable table into an AI-queryable tool for agentic workflows. Traditional RAG excels at unstructured data (at least Pixeltable does) but struggles with structured information. Now

From One Video to Thousands of Searchable Frames: - Your 30-minute video became 1,800 searchable frames - Zero data duplication (frames materialized on-demand) - Cross-modal search (find frames using text descriptions and/or other images) - Automatic synchronization (add new

Your multimodal AI App just hit bad data. Now what?!?! 1) Your AI workloads should handle real-world, messy data without crashing. 2) You should be able to easily isolate and analyze failures without searching through massive log files. 3) You should be able to incrementally

Pixeltable SDK: the "primitives" to build real multimodal AI apps (really fast) - create_table: persistent, versioned memory for app state and media - create_view: iterator-driven chunking; incremental updates, no duplication - add_computed_column: declare DAG nodes;

@BuildWithJit кuro i'm building a lot on Pixeltable stack lately. Curious what you are using for your processing flow?

1h40 youtube video: Prompt Engineering in Python | Automatic and Programmatic Prompt Optimization | Complete Course How to code, your own, automatic prompt optimizer. How the most advanced prompt optimization tool, DSPy, works and how to fully leverage its capabilities. How

𝗕𝗬𝗢 𝗲𝗺𝗯𝗲𝗱𝗱𝗶𝗻𝗴𝘀 𝗶𝗻 𝗣𝗶𝘅𝗲𝗹𝘁𝗮𝗯𝗹𝗲. Pixeltable maintains embeddings on updates: • Return pxt.Array[(d,), pxt.Float] for exact dims • Cache the model inside the UDF • Use batch_size for throughput • Drop‑in add_embedding_index

If you're building AI applications today, you've probably experienced this pain: spending 80% of your time on data infrastructure and only 20% on the AI that actually matters. You're not alone. Traditional data engineering worked great for the SQL era. Build tables, run ETL

Latest video-related built-in UDFs we added: clip(), extract_frame, segment_video(), concat_videos(), overlay_text(), and VideoSplitter!

🚀 Pixeltable + Pydantic integration! Type safety in Pixeltable just got even better! Define your data models once, get validation everywhere across your storage and orchestration layers: -> pip install pixeltable pydantic | Samuel Colvin

Sree Adam Wathan FFmpeg If you struggle with ffmpeg: x.com/pixeltablehq/s…

pip install pixeltable -> unified storage, orchestration, and retrieval for your multimodal ai workloads right there on your machine.

Agents as Data-Centric Applications in Pixeltable 1) knowledge.add_embedding_index("content") 2) chat_history.order_by(timestamp).limit(4) 3) docs.similarity(query) 4) tools = pxt. tools(analyze, fetch, search) 5) agent.add_computed_column(answer=llm(all_layers)) 6)

Work with Videos, Frames, Model JSON Outputs, Leverage the power of Modal's GPUs right within their new notebook platform with Pixeltable! Build your evaluation pipeline, storage, cache, and orchestration for your media data. modal.com/notebooks/pbru…

Building an infinite-memory, context-aware, multimodal chatbot is as easy as this in Pixeltable: github.com/pixeltable/pix… Why? Because Pixeltable is the only multimodal data infrastructure that unifies storage and orchestration for your AI workloads. pip install pixeltable

Think of Pixeltable as a data infra specifically designed for AI applications that work with images, videos, audio, and documents. It's a database system that natively understands multimodal data and can orchestrate workloads. As a software engineer, you've probably dealt with

A new episode of Database School is out! I spoke with Marcel Kornacker, the creator of Apache Impala and co-creator of Apache Parquet, to talk about his latest project: Pixeltable, a multimodal database for the AI age. youtu.be/7nsfzb2bVpQ

JOB OPPORTUNITY: Full Stack Developer 💰 ~$200k + 1% equity 📍 SF, 2 days/wk (Market St) 🎁 $5k referral bonus We’re hiring our first Full Stack Developer to: 🛠️ Build a TypeScript SDK 🎨 Create a local UI for our open-source library (TS/React/Vite/FastAPI) 🚀 Work on our SaaS

🍂 This fall, we’ve been sharpening our pixels at Pixeltable. What if your video, image, and audio datasets just worked…across teams, clouds, and time? Highlights from our latest Python SDK release: 🎥 Advanced video processing & frame extraction ☁️ Flexible storage

The Paul Telford.query decorator by Pixeltable is a powerful tool for: - AI Agent Memory: Reusable context retrieval across conversations - Multimodal RAG & Tools Systems: Sophisticated hybrid retrieval with consistent logic - Multi-Table Analytics: Complex quries as simple functions