HyperProbe GTM brain

HyperProbe helps software engineering teams diagnose live production incidents with an AI on-call agent and read-only runtime probes.

category

AI production debugging and incident response

market profile

  • text: Production incidents consume scarce engineering time when the state explaining a failure was never logged.
  • text: Runtime debugging competes with live instrumentation and AI incident investigation tools, while also complementing existing logs and traces.

personas

  • title: SRE or on-call platform engineer
    pains:
    • Intermittent production errors cannot be reproduced from logs
    • Redeploying instrumentation extends incidents and increases pager fatigue
  • title: VP Engineering
    pains:
    • Senior engineers lose roadmap time to incident war rooms
    • Unverified hotfixes let the same incident recur
  • title: Security or infrastructure lead
    pains:
    • Live debugging may expose sensitive values or modify production
    • Needs access policy, audit trails and deployment controls

icp

  • text: Software teams with production services and on-call responsibilities, particularly those running JavaScript, Java, Python or Ruby.
  • text: Organizations with several critical services and security review requirements fit paid team and enterprise offerings; company size unspecified.

message pillars

  • text: Find causes without a restart or code change.
  • text: Capture evidence missing from existing logs.
  • text: Keep live probes read-only.

objections

  • objection: Production probes could introduce latency or risk.
    response: Pilot on one service with bounded probe policies and measure overhead under your own load.
  • objection: Captured variables may contain customer data.
    response: Review redaction, access controls, approval gates and deployment options with security.
  • objection: We already pay for observability.
    response: Test a case where logs and traces identify a suspect line but lack the variable needed to confirm cause.

competitors

  • name: Lightrun
    why: Live production instrumentation and debugging.
  • name: Datadog
    why: Observability and AI incident investigation.
  • name: Dynatrace
    why: Production observability and AI-assisted analysis.

influencers

  • name: Karan Raina
    url: https://www.ycombinator.com/founders/karan-raina
    why: Founder and CTO of HyperProbe.

keywords

  • production debugging without redeploy
  • live application debugging
  • AI on call agent
  • runtime variable capture
  • incident root cause analysis
  • dynamic instrumentation

voice

  • direct and technical
  • empathetic to on-call engineers
  • specific and outcome-focused

signals

  • text: A team is hiring SREs or scaling on-call after recurring hard-to-reproduce incidents.
  • text: A team already uses coding agents and needs production evidence for incident investigations.

stack

  • JavaScript
  • TypeScript
  • Java
  • Kotlin
  • Python
  • Ruby
  • PagerDuty
  • Datadog
  • Slack

pricing

model: freemium
starting price: Free for one service; Professional $99 per service per month, three-service minimum

motion

hybrid

channels

  • developer documentation
  • LinkedIn
  • YC launch
  • SEO

confidence

medium

Founders

  • name: Shailendra Singh
    title: Founder/CEO
    role: CEO
    bio: Founder at HyperProbe. Also founded HyperTest. Previously headed and scaled engineering and product functions at a unicorn and few small startups.
  • name: Karan Raina
    title: Founder/CTO
    role: CTO
    bio: Founder and CTO at HyperTest (YC S26) MS CS Georgia Tech 2nd time founder Previously led a 50 member engineering team at Limetray

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