HyperProbe
HyperProbe is an AI-native production-debugging and on-call agent that helps coding agents investigate incidents in real time. It places read-only, non-blocking probes into running services to capture exact live variable state that logs and traces missed, without redeployment or restart.
At a Glance
- Engineering and SRE teams operating production services
- Companies using coding agents such as Cursor, Claude Code, Codex, Windsurf, or opencode
- Organizations with high-throughput or distributed backend systems
- Security-conscious enterprises requiring private-VPC or self-hosted deployment
- +1 more
AI Tools by HyperProbe
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HyperProbe
AI Production Debugger No Redeploy
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Latest News
Published 'How an AI SRE differs from the APM you already run'
Published 'What is an AI SRE'
Public YC/Launch HN launch: HyperProbe, an on-call agent for read-only debugging in production
Accepted into Y Combinator Summer 2026 and listed as an active company
Products & Services
An incident agent that takes an alert from PagerDuty, Datadog, or Slack, analyzes logs and traces, places targeted read-only probes when telemetry is insufficient, and returns an evidence-backed root-cause analysis.
In-process agents for JavaScript/TypeScript, Java/Kotlin, Python, and Ruby that dynamically instrument running services and capture variables, call stacks, logs, counters, or metrics without source changes, restarts, or redeployments.
An IDE workflow for installing the agent, selecting executable source lines, inserting Snapshot/Log/Counter/Metric/Tic & Toc probes, and viewing captured variable trees and call stacks.
Model Context Protocol integration that lets coding agents investigate incidents, place bounded probes, collect live evidence, iterate on hypotheses, and produce a Confirmed, Probable, or Inconclusive RCA.
Market Position
HyperProbe positions itself as a capture-class AI-SRE/runtime-observability layer rather than another tool that only reasons over existing logs, traces, metrics, and tickets. Its differentiator is live, read-only evidence collection at the relevant code line without redeployment; it therefore complements or competes with conventional APM/observability and incident-response tooling while targeting the gap those systems leave when the explaining value was never recorded.
Leadership
Founders
Shailendra Singh
Founder and CEO of HyperProbe; previously founded and ran Transporter.city (2017–2021) and HyperTest, and previously headed and scaled engineering and product functions at a unicorn and smaller startups. HyperProbe's founder biography also says he began at Applied Materials and has more than a decade of production-systems experience.
Karan Raina
Founder and CTO of HyperProbe and previously founder/CTO of HyperTest. He holds an MS in Computer Science from Georgia Tech, previously led a 50-person engineering team at Limetray, and was Head of Product and Technology at Transporter.
Executive Team
Shailendra Singh
Founder and CEO
Previously founded Transporter.city and HyperTest; earlier led engineering and product functions at a unicorn and smaller startups and worked at Applied Materials.
Karan Raina
Founder and CTO
Previously founder/CTO of HyperTest; holds an MS in Computer Science from Georgia Tech and previously led a 50-person engineering team at Limetray and product/technology at Transporter.
Founding Story
The founders say they repeatedly saw production incidents reduce to one unanswered question: what was the actual value at the moment the code failed? Logs and traces often lacked that state, forcing engineers into a log-add/redeploy/wait cycle. After spending about three years building production SDKs for HyperTest and experiencing the problem in production, Shailendra Singh and Karan Raina started HyperProbe to give coding agents live, evidence-backed runtime data and turn multi-hour war rooms into much faster confirmed diagnoses.
Business Model
Revenue Model
Per-service SaaS subscription, with managed-cloud, self-hosted, and private-VPC deployment options. Billing is based on the number of instrumented services rather than engineers, seats, hosts, containers, traffic, probes, or captures.
Pricing Tiers
1 service on managed cloud; unlimited probes and captures; 7-day capture history; MCP server, supported runtimes, default PII redaction, immutable audit log, and community support.
Unlimited services and members, 30-day capture history, team probe policy, RBAC, Google/GitHub SSO, self-hosted available on request, and shared Slack support.
Self-hosted or private VPC, chosen-region data residency, custom retention and redaction, organization-level policies and approval gates, SAML SSO/SCIM, security-review support, DPA, named engineer, and contracted SLA.
Target Markets
- Engineering and SRE teams operating production services
- Companies using coding agents such as Cursor, Claude Code, Codex, Windsurf, or opencode
- Organizations with high-throughput or distributed backend systems
- Security-conscious enterprises requiring private-VPC or self-hosted deployment
- Teams in SaaS, developer infrastructure, cloud/DevOps, and AI-native software
- Silent failures and incorrect responses that produce no exception
- Intermittent production errors that cannot be reproduced locally
- Wrong behavior caused by swallowed exceptions
- Race conditions and duplicate processing
- Third-party API contract drift and unhandled status values
- Business-metric drops without an obvious application error
- CheQ Digital
- Housing.com