Telegram groups flood you with hundreds of messages daily.
Raven turns that noise into structured data — and lets you ask questions in plain language.
Every group message gets read, analyzed, and either extracted into structured data or discarded as noise.
Продаю виллу 5 комнат в Dubai Hills, 450 кв.м, бассейн и сад. Цена 3 600 000 AED. Звоните: +971 50 111 2222
Enter your phone number. Raven shows all groups you're in. Pick which ones to monitor. Takes 30 seconds.
Pick a preset (HR, Real Estate, Crypto…) or define custom fields. Name each field and describe what to extract — Raven does the rest.
Raven monitors 24/7. New messages get processed within seconds. Browse Items, filter, export — or just ask in plain language.
No SQL, no exports, no pivot tables. Just ask Raven what you need — it answers from your extracted data.
Ask in English or Russian. Filter by price, date, location, any field you defined.
Counts, averages, breakdowns — Raven calculates across your entire dataset.
New messages arrive in real time. Your next query already knows about them.
Define exactly what fields to extract. Name, type, description — AI fills the rest automatically from every message.
Raven reads your groups 24/7. New messages are processed within seconds — no polling, no delays.
AI identifies and discards replies, reactions, and off-topic messages. Only real data reaches your Items list.
Natural language chat over your extracted data. "What are the top salaries this week?" — Raven answers instantly.
Start in seconds with built-in schemas for HR, Real Estate, Crypto, Legal, Auto, and Marketplace. Customize anytime.
Telegram sessions encrypted with AES-256-GCM. Your data stays yours — no third-party sharing, ever.
You define the schema — Raven extracts. No code, no integrations.
Collect job postings from talent groups. Ask: "All remote Python roles above $5k this week?"
Monitor property listings. Ask: "Cheapest 3-bedroom villa in JBR posted today?"
Track signals and calls. Ask: "All long calls on BTC from yesterday with target above 90k?"
Aggregate cases and precedents. Ask: "How many labor dispute cases were added this month?"
Track car listings. Ask: "BMW 5-series under 80k, under 50k km?"
Aggregate signals from industry channels. Ask: "What topics dominated last week?"