The next frontier for AI agents isn't just smarter algorithms—it's smarter context. Two founders with over a decade of collaborative coding experience have launched Hyper, a platform designed to transform scattered company knowledge into a unified AI memory system. This innovation aims to bridge the gap between powerful models and the messy, distributed information they need to deliver meaningful results.
Shalin and Kanyes, best friends turned co-founders, unveiled Hyper on Hacker News. Their platform acts as a "company brain," ingesting data from tools like Slack, email, documents, and calendars to provide AI agents with the comprehensive context they often lack. "Most AI models can handle complex tasks, but they struggle because critical company knowledge exists in Slack threads, outdated documents, or conversations that never get documented," explained Shalin. Hyper changes that by creating a persistent, searchable repository of company knowledge that agents can reference repeatedly.
Why current AI memory systems fall short
Existing solutions like Model Context Protocol (MCP) have limitations that Hyper addresses. For instance, MCP requires users to manually paste entire documents for each session, which isn't scalable. It also fails to capture the full picture because crucial decisions are often made verbally, scribbled on whiteboards, or discussed in fragmented Slack messages. Even when all information is available, AI agents lack the meta-reasoning capabilities to interpret context like company design preferences or writing styles without explicit instructions.
Hyper's approach differs by creating a knowledge graph that organizes facts, relationships, and source references. "We don't just store raw data—we structure it as subject-predicate-object relationships with timestamps and provenance," said Kanyes. The system updates in real-time, automatically invalidating outdated information while preserving historical context. For example, if a team initially plans to ship on Friday but later changes to Monday, Hyper updates the fact graph without discarding the original context, allowing users to audit past decisions.
How Hyper structures and secures company knowledge
Hyper's memory system operates on two levels: raw episodes (source items) and derived facts. Episodes serve as the immutable source of truth, while facts extract meaningful relationships—like who works where or which decision supersedes another. The system uses hybrid search, combining semantic embeddings with PostgreSQL's full-text search to deliver precise results tailored to each user's access permissions.
Security and compliance are built into the architecture. Every fact includes provenance tags and access-control restrictions, ensuring sensitive information remains protected. "Two team members asking the same question might get different answers based on their permissions," explained Shalin. The system also handles data freshness through webhooks and polling, detecting changes even in platforms that lack native deduplication.
Real-world impact: From hours to minutes
Early users report transformative results. A CEO using Hyper drafts emails in his authentic voice with full company context, reducing weekly work from hours to minutes. Another YC founder credited Hyper for enabling a one-shot launch video script because the platform had already absorbed months of product positioning and team communications.
Hyper offers a three-day free trial to help teams evaluate its capabilities. The platform's FAQ addresses privacy concerns, compliance requirements, and how it compares to other memory-focused tools. "We're not for everyone," acknowledged Kanyes. "But for teams pushing the boundaries of agentic development, Hyper is a force multiplier."
The road ahead for AI-powered collaboration
As AI agents take on more complex tasks, the need for reliable, contextual memory will only grow. Platforms like Hyper represent a critical step toward bridging the gap between raw AI capability and practical business applications. While still in its early stages, Hyper's approach to persistent, structured company knowledge could redefine how teams leverage AI for automation and decision-making. The founders invite users to test the system, provide feedback, and help shape the future of agentic development.
AI summary
Hyper, şirket içi bilgileri AI ajanlarının kullanımına sunan yenilikçi bir platform olarak AI destekli otomatikleştirmeyi yeniden tanımlıyor.
