Hyper

The Self-Driving Company Brain

Spring 2026ActiveB2BProductivityArtificial IntelligenceProductivityTeam CollaborationSan Francisco, CA, USA

Company

Hyper is the company brain that "just works" for AI-first teams. Hyper silently learns from every update in every tool your team uses -- Notion docs, Claude Code questions, emails, LinkedIn DMs, Cursor sessions, etc. Our agent-driven algorithms update and clean all that information into real-time knowledge that is shared across your entire team. That knowledge is quietly infused into all your existing AI tools on every chat turn, so your whole company gets smarter permanently.

Note: This is a preliminary assessment based on limited publicly available information. We did not have access to LinkedIn profiles or live product screenshots for this analysis. We will update this entry with a more thorough review soon.

Verdict

Medium Signal

Market Opportunity

B2B productivity/knowledge management for AI-first teams is a real and growing market, but the ICP is vague — 'AI-first teams' is not a tight segment. The concept of a persistent company knowledge layer has clear monetization potential (SaaS per seat), but no pricing or customer evidence is provided to validate demand.

Medium Signal

Founder Signal

Both founders are UC Berkeley CS/EE grads with relevant experience: Shalin was autonomy lead at Matic Robots (robotics startup), and Kanyes was research lead at Matic Robots plus an FDE (Field/Forward Deployment Engineer) at Snorkel AI, a serious ML data labeling company. Solid but not exceptional — neither has a previous exit, and no LinkedIn data was available to verify depth of roles or years of experience. FDE at Snorkel is more go-to-market than engineering, which is a mild concern for a deep-tech product.

Low Signal

Competition

The space is extremely crowded: Notion AI, Guru, Tettra, Mem, Glean, Confluence with AI, and a dozen YC-funded knowledge management startups all compete here. OpenAI and Google are actively building memory/context features into their products. No proprietary data moat, network effect, or defensible technical differentiation is articulated — the pitch relies on integration breadth, which is easily replicated.

Low Signal

Product

No named customer logos, no pricing page, no live demo, no specific revenue or usage metrics anywhere in the data. The description is entirely conceptual — 'silently learns,' 'quietly infused' — with no evidence of a working product or even a beta waitlist. Zero press coverage found.

OverallC Tier

Hyper is a concept-stage product in one of the most saturated categories in enterprise AI — ambient knowledge management and team memory. The founders have relevant experience at Matic Robots and Snorkel AI, but no prior exits and no LinkedIn data to validate depth. The product description is all metaphor and no evidence: no customers, no metrics, no demo, no press. The competitive threat from OpenAI Memory, Glean, and Notion AI is severe and these incumbents have massive distribution advantages. Without a specific technical moat or early traction signal, this looks like a well-articulated idea in search of differentiation.

Active Founders

Shalin Shah

Founder

Passionate about the marriage of deep design and engineering to create beautiful products. Cofounder of Hyper, previously autonomy lead @MaticRobots, and UC Berkeley EE/CS.

Kanyes Thaker

Founder

I believe in building exceptional products. Co-founder @ Hyper. Prev FDE at Snorkel AI and research lead at Matic Robots. Berkeley CS + Mathematics. Happy to chat: kt@heyhyper.ai

Hyper

TierC Tier

BatchSpring 2026

Team Size2

StatusActive

LocationSan Francisco, CA, USA

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