Claro runs the AI agents that operate on your data
Today, we're opening the first public module of Claro: Research Agents. 10+ task-specific agents run inside a native table - enrichment, PDF extraction, URL scraping, classification, location lists, dedupe. Every cell comes back with a confidence score, citations, and ranked sources. Built validation-first, not a chat wrapper. 200 free credits on signup, no card.
Hey Product Hunt 👋 I'm Matteo, co-founder of Claro.
We built Claro because we kept losing trust in our own AI outputs. @tameesh and I spent years at Delivery Hero and Yelp trying to wrangle product and supplier data at scale. Tameesh then did NLP/LLM research and published at MIT Review. Every time we plugged an LLM into a data workflow, we got beautiful-looking answers with no way to know which ones were right.
Claro is the AI execution layer for product and supplier data. It takes messy supplier feeds, spreadsheets, and documents, turns them into trusted catalog entities with stable IDs, and keeps them validated and correct over time.
Today we're opening the first public module: Research Agents. 14 task-specific agents that run inside a native table:
📋 Find your perfect list — describe ideal prospects, suppliers, or partners, get an enriched dataset 📍 Build a location list — draw an area on a map, generate POIs with attributes 📄 Capture tables from PDFs — pull tables from reports, pick which to keep 📑 Turn documents into structured data — extract fields across hundreds of docs at once 🌐 Scrape data from URLs — turn a list of links into structured rows 📊 Analyse CSV — upload a spreadsheet, validate and enrich it 🔀 Merge & Map — dedupe and reconcile records across two files and more.
What makes Claro different is what happens to every answer before it hits your table:
→ Multi-model consensus — we push extractions to multiple models in parallel and only accept where they agree → LLM-as-judge filtering — a lightweight quality gate catches nonsensical outputs before they reach you → Source ranking — first-party and authoritative sources above random blog posts, datasheets above application guides → Confidence scores — every cell scored at row, column, and entity level based on source reliability, cross-source consistency, model certainty, and retrieval quality → Full citations — click any cell to see the exact passage, URL, or document section it came from → BM25 + AI hybrid matching — for entity resolution against your existing catalog, with human approval loops for borderline cases
It's not a chat wrapper. It's validation-first infrastructure with a spreadsheet you can use today.
Three things I'd love today:
Try it — 200 free credits, no card.
Break it — throw your ugliest CSV or weirdest PDF, tell me what it got wrong (and what the confidence score said)
Tell me which agent you'd use first — we're deciding what to deepen next
I'm pitching live at The Pitch Berlin today, so I'll be bouncing between stage and comments, but I'll reply to every one before EOD.
If you run a marketplace, distributor, or multi-supplier catalog and the underlying platform sounds relevant, DM me — we'd love to talk.
Thanks for taking a look 🙏 — Matteo
About Claro - Research Agents on Product Hunt
“Claro runs the AI agents that operate on your data”
Claro - Research Agents launched on Product Hunt on April 20th, 2026 and earned 87 upvotes and 4 comments, placing #17 on the daily leaderboard. Today, we're opening the first public module of Claro: Research Agents. 10+ task-specific agents run inside a native table - enrichment, PDF extraction, URL scraping, classification, location lists, dedupe. Every cell comes back with a confidence score, citations, and ranked sources. Built validation-first, not a chat wrapper. 200 free credits on signup, no card.
On the analytics side, Claro - Research Agents competes within Productivity, Artificial Intelligence and Pitch Berlin — topics that collectively have 1.1M followers on Product Hunt. The dashboard above tracks how Claro - Research Agents performed against the three products that launched closest to it on the same day.
Who hunted Claro - Research Agents?
Claro - Research Agents was hunted by Rajiv Ayyangar. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of Claro - Research Agents including community comment highlights and product details, visit the product overview.
Rajiv Ayyangar
Hey Product Hunt 👋 I'm Matteo, co-founder of Claro.
We built Claro because we kept losing trust in our own AI outputs. @tameesh and I spent years at Delivery Hero and Yelp trying to wrangle product and supplier data at scale. Tameesh then did NLP/LLM research and published at MIT Review. Every time we plugged an LLM into a data workflow, we got beautiful-looking answers with no way to know which ones were right.
Claro is the AI execution layer for product and supplier data. It takes messy supplier feeds, spreadsheets, and documents, turns them into trusted catalog entities with stable IDs, and keeps them validated and correct over time.
Today we're opening the first public module: Research Agents. 14 task-specific agents that run inside a native table:
📋 Find your perfect list — describe ideal prospects, suppliers, or partners, get an enriched dataset 📍 Build a location list — draw an area on a map, generate POIs with attributes 📄 Capture tables from PDFs — pull tables from reports, pick which to keep 📑 Turn documents into structured data — extract fields across hundreds of docs at once 🌐 Scrape data from URLs — turn a list of links into structured rows 📊 Analyse CSV — upload a spreadsheet, validate and enrich it 🔀 Merge & Map — dedupe and reconcile records across two files and more.
What makes Claro different is what happens to every answer before it hits your table:
→ Multi-model consensus — we push extractions to multiple models in parallel and only accept where they agree
→ LLM-as-judge filtering — a lightweight quality gate catches nonsensical outputs before they reach you
→ Source ranking — first-party and authoritative sources above random blog posts, datasheets above application guides
→ Confidence scores — every cell scored at row, column, and entity level based on source reliability, cross-source consistency, model certainty, and retrieval quality
→ Full citations — click any cell to see the exact passage, URL, or document section it came from
→ BM25 + AI hybrid matching — for entity resolution against your existing catalog, with human approval loops for borderline cases
It's not a chat wrapper. It's validation-first infrastructure with a spreadsheet you can use today.
Three things I'd love today:
Try it — 200 free credits, no card.
Break it — throw your ugliest CSV or weirdest PDF, tell me what it got wrong (and what the confidence score said)
Tell me which agent you'd use first — we're deciding what to deepen next
I'm pitching live at The Pitch Berlin today, so I'll be bouncing between stage and comments, but I'll reply to every one before EOD.
If you run a marketplace, distributor, or multi-supplier catalog and the underlying platform sounds relevant, DM me — we'd love to talk.
Thanks for taking a look 🙏 — Matteo