GitHub App–first Connect
One Infravox GitHub App for every customer. Install on the org, pick repos — no PEM, webhook, or OAuth secrets from the buyer.
Infravox connects AWS, Azure, GCP, Kubernetes, and GitHub into one operating surface — investigate in War Room, watch posture and spend, collect compliance evidence, and remediate with guardrails. Founded 2026. Google for Startups member. Building in the open with design partners.

Not a vision deck. The work on develop this quarter — connect UX, packaging, remediation depth, and SCM expansion.
One Infravox GitHub App for every customer. Install on the org, pick repos — no PEM, webhook, or OAuth secrets from the buyer.
Starter / Growth / Scale with hard caps on accounts, nodes, AI ops, and retention — plus add-ons so we stay at 70–80% gross margin.
Live command surface, cloud cost insights, posture monitoring, and control packs tied to the infrastructure graph.
Agents propose fixes with blast-radius context; humans approve. Higher autonomy rolls out behind policy on Scale+.
GitLab, Bitbucket, and Azure Repos on the same security path as GitHub — planned behind a clear GA gate, not sold early.
Cluster-level signal for SRE and security — after a controlled PoC, not as a silent Growth include.
Selected for the Google for Startups program — Google Cloud infrastructure, AI credits, mentorship, and a global founder network.
Built for clusters and cloud accounts — not a bolt-on dashboard.
CIS and framework-aligned evidence (SOC 2 / ISO / HIPAA / PCI) — assessment, not a seal.
Inventory, posture, cost, and change context across providers.
Specialist agents coordinated in War Room with confirm-gated remediations.
Enterprises bought a dashboard for every layer — and still page humans when something breaks. Context stays siloed. Nothing owns the loop from signal → decision → action.
Observability, CSPM, FinOps, and tickets stay siloed. Humans still stitch context at 3AM.
Idle and oversized spend survives because recommendations lack guardrails and ownership.
CSPM lists misconfigs. Engineers need topology, deploy history, and who owns the risk.
Evidence is gathered for audits instead of continuously from the live estate.
No rip-and-replace. Collect → investigate → secure → comply → optimize → remediate — with human confirmation where it matters.
Link AWS, Azure, or GCP accounts and install the Infravox GitHub App. Kubernetes and Slack optional. Most pilots are live in under 30 minutes.
SRE, Security, FinOps, and Compliance agents pull inventory, posture, cost, and change signals into one graph.
War Room correlates deploys, findings, and topology — root cause with proof, not another disconnected alert.
Confirm-gated actions (and higher autonomy where policy allows). Every step audited. Capacity-capped so unit economics stay sane.
Operators should not babysit five tools to answer one incident. Infravox connects cloud, code, cost, and risk so teams investigate, secure, and remediate from one operating surface.
Fortune-scale cloud will be operated by coordinated agents — not dashboard armies. We’re building that OS carefully: confirm-gated first, autonomous where policy earns trust.
We started in 2026 to replace half the infrastructure stack with autonomous operations — shipping modules first, then earning the right to act without a human in the loop.
Infravox AI founded to build an AI operating system for cloud infrastructure — not another monitoring dashboard.
Core engine, early Kubernetes tooling, and first remediation loops shipped fast so design partners could touch real cloud.
Security, FinOps, Compliance path, topology graph, CLI, and War Room — Abhijit joined as Head of Engineering.
Vendor GitHub App install for customers, margin-safe pricing with capacity caps, Trust Center path, and multi-SCM + deeper autonomy on the roadmap.
Five people who've lived the pager and decided to build the OS instead of living with the tool sprawl.

Technical founder focused on Kubernetes, cloud-native systems, and AI-driven infrastructure automation. Previously led platform engineering at scale.

Owns product strategy and GTM. Bridges customer reality with what we ship — packaging, pilots, and enterprise motions that can scale.

Full-stack engineering leader across backend, frontend, GenAI agents, and ML infrastructure — shipping the platform customers run in production.

Leads AI agents, LLM infrastructure, and autonomous engineering intelligence — the systems that investigate and propose remediations.

Turns operator pain into roadmap. Works across engineering, GTM, and design partners so the product stays specific — not generic AI theater.
Five constraints we apply to product, pricing, and autonomy — not a nine-item poster wall.
Remediations start confirm-gated. Audit trails, blast radius, and reversibility come before auto-mode.
Every insight should show reasoning and source data — not a black-box score.
Public plans use capacity caps and add-ons. We won’t sell unlimited AI ops we can’t deliver sustainably.
Meet teams in AWS, Azure, GCP, GitHub, Slack, and Kubernetes — expand from there.
GA vs Beta labeled. Compliance means control packs, not fake certifications. Roadmap items aren’t sold as live.
Foundation and modules are in customers' hands. Autonomy depth and Fortune-scale deploy are the work ahead.
Live agents cover the core ops surface. Others are building toward GA — we label status so buyers aren't surprised.
Incident triage, RCA drafts, MTTR reduction with evidence.
Multi-cloud inventory and provider-native health.
Workloads, HPA, and control-plane health signals.
Misconfigs, posture, and risk with topology context.
Control packs and continuous evidence collection.
Waste, rightsizing, and savings tied to the graph.
Plan review, drift signals, policy-aware apply readiness.
Change impact and rollback readiness.
Infra-aware review across security, cost, blast radius.
Orchestrates agents, humans, and remediations live.
Design partner, enterprise buyer, or investor — start a 7-day pilot or talk to the team.