Pre Seed · Investor memo
Infravox AI, the AI operating system for cloud infrastructure
Infrastructure should not just tell you something is wrong. It should understand what happened, decide what to do, and safely fix it: an autonomous operating layer, not a monitoring chatbot.
- Raise goal
- $750K about 10% · Prefer SAFE
- Modules
- 8 live surfaces
- Agents
- 30+ specialized
- Hubs
- SF + Gurugram dual hub
Design partners are active and not positioned as paid customers today. 100+ integrations are roadmap, not current fact.
Problem
It is 2:13 AM. A production database fails.
Alert fires. The on call jumps between tools. Logs, metrics, tickets, Slack: pieces without a shared picture. Someone decides. Someone fixes. Someone verifies. By morning it looks resolved until it happens again.
The problem is not that companies lack infrastructure tools. Their tools can surface that something is wrong, but humans still have to investigate, decide, and fix it.
| Legacy stack | With Infravox |
|---|---|
| On call triage across five tools | Agents correlate across the infra graph |
| 40+ minutes correlating logs and tickets | Root cause framed with evidence first |
| Blast radius unknown while customers feel it | Remediation proposed or gated with audit |
| Human operated recovery | Machine assisted recovery |
| Illustrative stack cost | Monthly |
|---|---|
| Monitoring | $499 |
| Security | $1,499 |
| Compliance | $4,999 |
| Stacked tools / yr | $81,984 |
Solution
Infravox closes the loop
Detect, Understand, Decide, Act, Verify, Learn: one OS loop across eight modules and 30+ specialized agents.
| Step | What it does |
|---|---|
| Detect | Correlate signals across clouds, clusters, and apps. |
| Understand | Map topology and blast radius on the infra graph. |
| Decide | Rank root causes with evidence, not alert noise. |
| Act | Propose or gate remediations with policy controls. |
| Verify | Confirm outcomes and leave an audit trail. |
| Learn | Compound memory so the next incident is faster. |
Traction
Verified execution, not invented ARR
| Signal | Detail | Status |
|---|---|---|
| 8 | Modules in production architecture | Verified |
| Design | Partners (not paid customers as current fact) | Verified |
| 6 + 1 | Enterprise evaluations and 1 onboarding (NDA) | Verified |
| 30+ | Agents with 100+ integrations on the path | Roadmap |
| When | Milestone | Notes |
|---|---|---|
| Past | AI OS MVP and eight module surface | Core agents, War Room, remediation path, and operational memory shipped in production architecture. |
| Past | Google for Startups and LvlUp Labs | Selected into programs with First Check / LvlUp investment commitment. |
| Now | Pipeline in motion under NDA | Six enterprise evaluations and one onboarding. Names and detail in the data room. |
| 90 days | First paid customers and SOC 2 prep | Convert design partners and evaluations. SOC 2 Type II is a target, not a claim. |
We do not publish invented accuracy rates, waste savings, or customer logos. Request the data room for named diligence materials.
Market · model and assumptions
Bottom up pricing ladder first. Category size second.
Published monthly pricing annualizes cleanly. Large TAM figures without assumptions are not treated as fact here.
| Plan | Monthly | ACV (×12) | Note |
|---|---|---|---|
| Starter | $499 | $5,988 | Verified pricing |
| Growth | $1,499 | $17,988 | Common land expansion |
| Scale | $4,999 | $59,988 | Heavier ops / multi cloud |
| Metric | Value | Note |
|---|---|---|
| Obtainable TAM | $8B | Forecast |
| Land deal size | $1.5K to $5K / mo | Annualize ×12 |
| Time to expand | 90 to 180d | Target |
| ICP | Series B to D | Multi cloud |
Go to Market
Land. Prove. Expand.
| Stage | Approach |
|---|---|
| Land | Wedge with platform / SRE on War Room + graph. Design partners and evaluations first. |
| Prove | Convert to first paid customers within about 90 days (target). Measurable incident, security, and FinOps outcomes under NDA. |
| Expand | Attach security, compliance, and FinOps modules on the same OS loop and tenant graph. |
Financials · forecast and targets
Outcome priced, high margin SaaS
Unit economics and MRR path are illustrative diligence inputs, not audited actuals or promises of future performance.
- Company
- Infravox AI, Inc.
- Model
- Usage + seat hybrid
- Gross margin
- 85%+ target
- Structure
- US Corp, Delaware
Pricing and unit economics
| Plan | Price / mo | ACV | Est. COGS | Gross profit | Margin |
|---|---|---|---|---|---|
| Starter | $499 | $5,988 | ~$70 | ~$429 | ~86% |
| Growth | $1,499 | $17,988 | ~$200 | ~$1,299 | ~87% |
| Scale | $4,999 | $59,988 | ~$700 | ~$4,299 | ~86% |
Illustrative MRR plan
| Month | MRR |
|---|---|
| M1 | $8K |
| M4 | $25K |
| M8 | $80K |
| M12 | $180K |
| M24 | $350K |
| Operating plan | Value |
|---|---|
| Monthly burn | ~$25K to $35K |
| Target runway | 18 mo |
| MRR · Month 12 | $25K |
| ARR · Month 24 | ~$2.1M |
Competition
Structural differentiation, not competitor attacks
Illustrative capability matrix from public product categories.
| Capability | Infravox | Observability | CSPM / XDR | FinOps | Ticketing |
|---|---|---|---|---|---|
| Detect anomalies / posture | Yes | Yes | Yes | Partial | No |
| Decide RCA with topology | Yes | Partial | Partial | No | No |
| Gated remediation | Yes | No | Partial | Partial | No |
| Compliance evidence loop | Yes | No | Partial | No | No |
| Unified Sec + Cost + SRE loop | Yes | No | No | No | No |
Moat
Graph, Memory, Execution, Safety, Learning
| Layer | Why it compounds |
|---|---|
| Graph | Shared infrastructure topology every agent reads and writes. |
| Memory | Incident and change memory that compounds across tenants safely. |
| Execution | Actions, not dashboards, with tool use across clouds. |
| Safety | Propose first defaults, tenant isolation, audit trails. |
| Learning | Feedback closes the OS loop so autonomy earns trust. |
Team
Operators building for operators
Founder market fit · Shivam Singh. Built and lived the 3AM pager world across cloud ops, then started Infravox so autonomous systems carry the loop humans should not have to glue together at 2:13 AM.
| Name | Role | Focus | |
|---|---|---|---|
| Shivam Singh | Founder and CEO | Built systems that paged him at 3AM, then decided no engineer should live that life again. | |
| Sameer Bhanot | Chief Operations and Product | Sits with operators until the pain is unmistakable, then turns that pain into a product companies pay for. | |
| Abhijit Singh | Head of Engineering | Turns fragile demos into systems you can trust at 2AM. If it is not production ready, it is not finished. | |
| Mohammed Arsalan | Head of AI and Autonomous Systems | Builds AI that acts: agents, reasoning loops, and tool use that replace toil with intelligence. | |
| Muskan Khandelwal | Sr. Product Manager | Turns operator pain into a product roadmap, aligning engineering, go to market, and customer needs. |
The Raise
Pre Seed · $750,000 · about 10%
Prefer SAFE (terms in data room). About 18 months of runway toward seed: first paid customers, SOC 2 prep, and repeatable GTM. Milestones below are targets, not commitments.
| Use of funds | Allocation |
|---|---|
| Engineering | 45% |
| AI Infrastructure | 25% |
| Sales / GTM | 15% |
| Security and Compliance | 10% |
| Operations | 5% |
Appendix
FAQ and diligence links
What is Infravox AI in one sentence?
The AI Operating System for Cloud Infrastructure: 30+ agents across eight modules that monitor, investigate, secure, comply, optimize, and remediate with enterprise controls.
What are you raising?
Pre Seed $750,000 for about 10%. Prefer SAFE (terms in data room). Use of funds: Engineering 45%, AI infra 25%, GTM 15%, Security and Compliance 10%, Operations 5%.
What is hard vs soft traction?
Hard / verified: live AI OS architecture, 8 modules, 30+ agents, design partners, 6 evaluations + 1 onboarding (NDA), Google for Startups + LvlUp / First Check commitment, SF + Gurugram. Soft / forward looking: MRR forecast, first paid customers, SOC 2 Type II (targets), 100+ integrations (roadmap).
How do I diligence next?
Request the data room, download the deck, book a founder meeting, and schedule a live product walkthrough.
Next steps