The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
Back to feedPost
Plurai — you describe what your AI agent should and shouldn't do in plain language, and it generates the eval test suite, runs tests at sub-100ms latency, and deploys a custom guardrails model from your specs — at 8x lower cost than GPT-as-judge.
Wonder — an AI design agent in public alpha that works directly on your canvas, generating UI, graphics, and pitch decks, with native integrations into Cursor and Claude Code so your designs stay connected to the codebase.
KarmaBox — runs AI agents including Claude Code from your phone, routing tasks to Claude, Codex, or Gemini and using your existing devices as a private compute pool, no separate infrastructure required.
Cloud Computer by Manus — gives your bots a dedicated persistent machine in the cloud so automated workflows keep running without tying up your laptop, from the team behind the Manus general AI agent platform.
Gemini Deep Research Agent — now available in the Gemini API in two variants: standard for fast synchronous queries and Max for longer async research runs, with MCP support to connect it to your own data sources beyond the web.
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
Related posts
AI Assistant Using Your Business Knowledge Base — RAG on Your Documents
THE PROBLEM
Q&A bots break down when knowledge lives in documents: a 100-page manual has no "questions" to match, it can't fit into a prompt, and generic chatbots hallucinate instead of admitting what they don't know.
THE SOLUTION
A RAG (Retrieval-Augmented Generation) knowledge base: documents are split into meaningful chunks, embedded into a vector index, and the assistant answers from the right sections — by meaning, not keywords.
Any format as-is: PDF, DOCX, TXT, Markdown — 100+ pages is fine
Answers grounded in YOUR documents — it says "I don't have that information" rather than inventing
Source references — every answer shows which document and section it came from
Runs on your infrastructure — documents never leave your control
One command to re-index after updating documents — documented, no programmer needed
LIVE DEMO
Ask it about my products, pricing, deployment and support — it answers from 6 real documents with sources:
https://kb-assistant-demo.dvc-ai.workers.dev
The 'I don't have that information' line is the part most RAG builds skip, and it's the one that matters. How do you set the cutoff? On mine, a fixed similarity threshold broke once I filtered results by user role. Scores shifted and it refused questions it could answer.
Escape – Seamless Hotel & Travel Booking Experience
Escape is a modern mobile experience designed to make hotel discovery and booking completely frictionless. The design balances clean minimalism with intuitive user flows—featuring smart search filters, visual destination browsing, and transparent property details. Every interaction is optimized to guide users from initial inspiration to confirmed reservation in just a few taps.
