Hyper
A 'company brain' that keeps AI coding and work agents up to date on decisions your team already made — so an agent doesn't confidently redo work you rejected yesterday because nobody told it.
🔗 Visit Hyper
Description
AI agents can now write code, draft emails, and run scripts on their own, but they have no idea which plan your team rejected last week or which approach your lead engineer vetoed in a Slack thread — that context lives scattered across people's heads, old messages, and half-updated docs. Hyper's pitch is to become the one place that knowledge lives and stays current, injecting it into the AI tools your team already uses so an agent stops confidently re-proposing ideas you've already ruled out.
Hyper is a YC-backed (P26) 'company brain' platform built around persistent, graph-backed memory of a company's actual decisions, taste, and which facts have gone stale — positioned as solving what its founders describe as the real 2026 agent bottleneck: not model quality, but agents lacking durable organizational context. It learns from updates across a team's existing tools and injects real-time knowledge into whatever AI tools are already in use, rather than requiring a switch to a new agent platform. The company reported reaching $1K MRR within 12 days of its Hacker News launch. Detailed public pricing is not available.
💬 Our review
The short version: Hyper is a bet worth watching if your team already relies on multiple AI coding/work agents and keeps running into the same annoying problem — an agent confidently redoing something that was already decided against — but it's early enough that 'worth paying for' depends on a sales conversation, not a public price list.
The framing here is sharp: most 'company knowledge base' tools focus on human search (find the doc), while Hyper focuses specifically on feeding that context into agents so the agents themselves stop making avoidable mistakes — a more agent-native angle than a typical wiki or Notion integration. Fast early traction ($1K MRR in 12 days) is a reasonable signal of real demand for the problem, though it's a tiny, early data point rather than proof of a mature product. The honest limitation: without public pricing or much independent usage detail beyond the launch coverage, it's hard to judge fit or cost before actually talking to the team — treat it as a promising early-stage bet for teams already deep in agentic workflows, not a safe default purchase.
💰 Pricing
📊 Global score
🤖 AI-enriched data
Aucune grille tarifaire publique trouvée ; startup très récente (traction rapportée : 1000$ MRR en 12 jours après son lancement).
Pros
Angle spécifiquement pensé pour les agents IA, pas juste une base de connaissance humaine
Traction précoce rapide (1000$ MRR en 12 jours)
S'intègre aux outils IA déjà utilisés plutôt que d'en imposer un nouveau
Mémoire graph-backed, pensée pour rester à jour (pas juste un dump statique)
Cons
Pas de grille tarifaire publique, décision d'achat nécessite un contact commercial
Startup très jeune, peu de recul d'usage indépendant
Efficacité réelle difficile à évaluer sans essai direct