Tired of juggling countless Dapps for your blockchain needs? Meet Type AI, the world's first all in one AI bot that simplifies blockchain interaction with voice & text commands. #AI #Defi $Type

We’re still here. We’re still building. Believe in us and you will be rewarded very soon.

Gm world. Have a $type day.

We have begun integration for Robin Hood chain support, stay tuned.

What's Coming Next for Type AI? Sprint 1 — Smarter Core (AI / NLP) June 18 – July 1 Refining the model for crypto context. Better intent recognition and improved keyword search so commands land even when they're misspelled or slangy. Fuzzy ticker matching across token names and symbols. Context retention and multi-turn memory so conversations hold state, with disambiguation prompts when a request is ambiguous. Adding degen-speak understanding and beginning prompt-injection hardening. Sprint 2 — Faster & Sturdier (Performance / Infra) July 2 – July 15 Cutting latency with a caching layer and faster RPC routing. Fallback RPC providers for reliability and rate-limit tuning to keep things stable under load. A smaller fine-tuned model for cheap queries plus fallback routing to control inference cost. Queue optimization and a chart-rendering CDN for speed at scale, with uptime and horizontal scaling improvements throughout. Sprint 3 — Safety Suite v1 (Flagship) July 16 – July 29 The core scanners go live. Honeypot and rug detection, LP lock checker, and top-holder concentration analysis. Tax-trap detection surfaced inside a plain-English contract audit, all rolled into a single wallet and token risk score. Simulate-before-you-sign wired into every swap and snipe so users preview the outcome before committing. Sprint 4 — Safety Suite v2 (Protective Layer) July 30 – August 12 Always-on protection. Approval-risk alerts, a scam-token blocklist, and phishing-link detection in groups. This turns safety from a one-time check into continuous coverage and becomes the core reason to run trades through Type AI. Sprint 5 — Type AI MCP Server August 13 – August 26 Type AI becomes a callable tool for Claude, ChatGPT, and other agents. Charts, swaps, portfolio, and the full safety suite exposed through MCP, with read-only versus execute permissions. Use Type AI features with your favorite AI provider. Sprint 6 — Type AI Skill + UX Polish August 27 – September 9 The packaged Skill ships, teaching external models to drive full Type AI workflows end to end. Landing alongside a UX refresh: smoother onboarding, command shortcuts, inline help, cleaner response formatting, and proper loading states so the experience matches the new capabilities.

Every year, crypto adds more infrastructure. More chains, more protocols, more complexity. But most users still want the same thing they wanted from day one: to get something done quickly without navigating ten different interfaces. That’s why Type AI is built around outcomes, not interfaces.

The next evolution of crypto UX isn’t another dashboard. It’s execution without friction. Type AI: ✅Understands intent ✅Plans the transaction flow ✅Executes across protocols The interface slowly disappears.

Most AI products plateau after launch. We’re just getting started. Opus 4.7 is already live. ✔ faster responses ✔ better intent understanding ✔ cleaner execution across flows Type AI’s inbuilt architecture leverages the latest AI models to deliver the best possible results. ~43% estimated efficiency improvement based on our internal calculations. This upgrade directly improves how Type AI thinks and executes. @AnthropicAI

We’ve been building quietly, now it’s time to ship Our last update was received incredibly well, and we’ve been building on that momentum behind the scenes. The focus has been on upgrading the core intelligence of the agent using large volumes of real user interactions, manually reviewed edge cases, and conversations where performance fell short. What’s shipping next 👇 🧠 Stronger goal-driven AI Understands outcomes like “reduce risk”, “secure profits”, or “find yield” instead of just executing isolated commands. Context retention and intent parsing are significantly improved. 🔗 Advanced DeFi execution Multi-step actions across swaps, lending, staking, and liquidity handled in one coordinated flow rather than separate transactions. 📊 Polymarket support Natural language entry, position management, exposure tracking across outcomes, and AI-assisted decision support for prediction markets. ⚡ Pre-execution planning Simulates routes before acting to select safer, cheaper, higher-probability execution paths across chains and protocols. 🛡️ Confidence-aware responses When uncertainty is high, the agent now asks precise follow-ups or presents options instead of making risky assumptions. 📚 Continuous learning loop Flagged conversations and weak outcomes are reviewed and converted into training signals, allowing the system to improve from real usage over time. These upgrades push Type AI closer to a true autonomous financial co-pilot that can understand, plan, and execute reliably not just respond. Rolling out in phases over the coming weeks 🚀

"Should I invest in this token?" Type AI analyzes : ✅Market cap & liquidity ✅Trading volume patterns ✅Pros, cons, and risk factors ✅Short & long-term outlook ✅Overall score out of 10 Coming soon: Real-time sentiment analysis from Twitter, whale wallet tracking.

Type AI integrates with Lido & Aave directly. “Invest 2 ETH in Lido” → 4.2% APR, staking live in seconds. “How much have I earned from Lido?” → Real-time rewards tracking. No platform switching. No complex UIs. Just type and earn.

Bridge 100 USDC from Ethereum to Polygon with Type AI. Just one command. ✅ Auto detects chains ✅ Estimates fees upfront ✅ Tracks transaction status in real time ✅ Executes seamlessly From Ethereum, Solana, BSC, Arbitrum, Optimism, or Polygon, Type AI handles it all.

The Type AI agent now has a much deeper understanding of user intent, context, and follow-up behavior. We’ve fed it significantly more structured data from real conversations, including past responses, corrections, and moments where execution didn’t meet expectations. Every weak interaction was manually flagged, reviewed, and converted into learning signals. This has resulted in: * Stronger intent parsing across complex, multi-step requests * Better memory of conversational context without repeating questions * More accurate chain, token, and action inference * Fewer hallucinations and safer default assumptions What’s quietly improved under the hood 👀 🧠 Adaptive intent ranking based on historical user behavior 🧩 Self-correction loops when confidence is low 📊 Response scoring tied to execution success, not just accuracy 🛡️ Safer decision boundaries for high-risk actions ⏱️ Faster reasoning on chained intents and cross-chain tasks The bot doesn’t just answer better. It understands better. And it keeps improving with every interaction.