Pattern AI
Enterprise-grade revenue intelligence and conversational pattern recognition for high-velocity sales teams.
The AI meeting companion that captures insights and automates CRM workflows.
Grain is a sophisticated conversational intelligence platform designed to transform customer-facing meetings into structured, actionable data. By 2026, Grain has evolved beyond simple transcription, positioning itself as a critical middleware between video conferencing and CRM systems like Salesforce and HubSpot. Its architecture leverages multi-modal LLMs to not only transcribe dialogue but to interpret intent, sentiment, and technical requirements discussed during calls. The platform's competitive edge lies in its 'no-latency' synchronization, where AI-generated summaries and specific data points are mapped directly to CRM fields in real-time. For revenue teams, Grain serves as an automated documentation layer, ensuring that institutional knowledge is preserved and that sales-to-success handoffs are seamless. The technical stack focuses heavily on security and integration, providing enterprise-grade controls over data retention and access. As the 2026 market shifts toward verticalized AI, Grain differentiates itself through its deep focus on the 'Customer Record of Truth,' making it an essential tool for organizations scaling their revenue operations through data-driven insights.
Maps specific meeting insights directly to custom CRM fields using NLP intent matching.
Enterprise-grade revenue intelligence and conversational pattern recognition for high-velocity sales teams.
Turn every conversation into a structured knowledge asset with predictive conversational intelligence.
The intelligent API for conversational intelligence and automated meeting synthesis.
The audio-first interview intelligence platform for modern talent acquisition teams.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Supports real-time transcription and translation across 20+ languages using whisper-based models.
Elasticsearch-powered indexing of all spoken words across the entire organizational library.
One-click clipping and stitching of video highlights to create shareable customer feedback loops.
Differentiates between multiple speakers using voiceprint and metadata analysis.
Uses LLM prompting to generate summaries focused on specific metrics like BANT or MEDDIC.
Real-time timestamping during live calls via a companion app or web interface.
Critical customer requirements are often lost between the sales cycle and the onboarding phase.
Registry Updated:2/7/2026
Analyzing hours of user interviews is time-consuming and prone to bias.
Need for high-fidelity documentation of strategic decisions.