Introducing Bird SQL, a Twitter search interface that is powered by Perplexity’s structured search engine. It uses OpenAI Codex to translate natural language into SQL, giving everyone the ability to navigate large datasets like Twitter. perplexity.ai/sql
With Bird SQL, you can quickly find information on Twitter that would have been impossible to find with conventional search engines or web browsing:
"most liked tweets about #worldcup" perplexity.ai/sql?uuid=9b03e…
If you are interested in using our search engine on your structured or unstructured data, contact us at support@perplexity.ai, our Discord server, or via Twitter. Join our Discord to learn more about search and large language models: discord.com/invite/kWJZsxP…
This is a demo, not a commercial product. There are limitations to our Twitter data, database performance, and the expressiveness of SQL. Bird SQL does not interpret the content of tweets. For unstructured search, try Perplexity Ask.
Perplexity Computer now connects to your health apps, wearable devices, lab results, and medical records.
Build personalized tools and applications with your health data, or track everything in your health dashboard.
Combine personal health data with premium sources and medical journals for endless new ways to interact with your health information.
Build a custom marathon training protocol based on fitness data, generate a visit prep summary ahead of a doctor's appointment, or create personalized nutrition plans.
The Perplexity API platform is now a full-stack, model-agnostic API platform for building agents.
It replaces your model provider, search layer, and embeddings, built on the same infrastructure that powers Perplexity.
The Perplexity API platform consists of four APIs with one API key.
Agent API — orchestrate models for multi-step workflows
Search API — real-time web context
Embeddings API — retrieval at scale
Sandbox API — code execution for agents (coming soon)
Perplexity Agent API is a managed runtime for building agentic workflows with integrated search, tool execution, and multi-model orchestration.
Swap between the latest frontier models, configure curated presets, tool access, step limits, and token budgets, all from one endpoint.
More than half of all agent activity focuses on cognitive work.
Agent use is dominated by Productivity & Workflow (36% of queries) and Learning & Research (21%).
Users rely on the assistant to think through something, synthesize findings, and take action on those learnings.
Most agent queries come from personal use (55%), followed by professional (30%) and educational (16%) contexts.
New users often start with low-stakes questions like travel or trivia. Over time, they shift to more complex topics like productivity, learning, and career advice.
With Microsoft retiring the Bing Search APIs in August, legacy search engines have abandoned the developer community who need real-time access to information.
We're stepping in to provide a search API designed for the new retrieval paradigms introduced by frontier AI systems.
We built Perplexity Search API around three criteria: