RevAgent Autonomous Revenue Operator for B2B SaaS
Replace a full-time RevOps analyst. Stop deal slippage before it hits the board.
revagent.it
Deals slip. Forecasts are wrong. RevOps is manual.
- Sales reps spend only 2 hours/day actually selling — 70% of their time is wasted on admin, CRM updates, and internal reporting
- 93% of sales organizations cannot achieve 90%+ forecast accuracy
- CRM data decays 22-70% annually — dirty data costs businesses $13M/year (Gartner)
- Mid-market B2B companies lose 7-10% of annual revenue to deal slippage and revenue leakage
- Average win rate on B2B deals: 21% — most pipeline is noise
A $50M ARR company loses $3.5-5M/year to problems a good RevOps analyst would catch.
The problem: mid-market companies (50-500 employees) can't afford a $200K RevOps hire, and enterprise tools like Clari ($120K+/yr) and Gong ($250/user/mo) are priced for Fortune 500.
RevAgent is an AI RevOps analyst that runs your pipeline on autopilot.
Six AI agents work your pipeline daily:
| Agent | What It Does |
|---|---|
| Risk | Scores every deal 0-100. Flags slippage before humans see it. |
| Hygiene | Fixes stale close dates, wrong stages, missing next steps in CRM. |
| Follow-up | Drafts personalized emails for deals going cold. You approve, we send via Gmail. |
| Escalation | Routes high-risk deals to managers with context. Slack alerts included. |
| Forecast | AI-adjusted forecast vs raw CRM. Confidence intervals. Bias detection. |
| CRO Brief | Weekly executive briefing: slipping deals, hidden risk, recommended interventions. |
Plus a Chat Agent — ask questions about your pipeline in natural language.
Connect CRM. Connect Gmail. First risk scan in under 5 minutes. You approve — we execute.
+------------------------------------------------------------------+
| RevAgent CRO Dashboard [Run Risk Scan] |
+------------------------------------------------------------------+
| |
| Pipeline at Risk Deals Flagged Actions Pending |
| $2.4M (18%) 12 high-risk 7 need your call |
| |
| +-- At-Risk Deals --------+ +-- Forecast ----------------+ |
| | Acme Corp $340K 87% | | CRM: $4.2M | |
| | TechFlow $180K 74% | | AI: $3.6M (-14%) | |
| | DataScale $95K 71% | | Conf: $3.1M - $4.0M | |
| +--------------------------+ | [Bias Detected] | |
| +-----------------------------+ |
| +-- Pending Actions -------+ +-- Weekly CRO Brief -------+ |
| | Fix close date: Acme [Approve] [Reject] | |
| | Follow-up: TechFlow [Approve & Send] | |
| | Escalate: DataScale [Approve] | |
| +--------------------------+ +-----------------------------+ |
+------------------------------------------------------------------+
Two modes:
- Human-in-the-loop — AI recommends, you approve each action
- Fully autonomous — AI executes with 3-gate safety: field allowlist + safety score + rollback
-
LLMs are finally good enough. GPT-4o-mini can reason about deals, draft emails, and detect pipeline patterns at a cost that makes per-deal analysis viable ($0.01-0.03/deal/day).
-
RevOps is the fastest-growing function in B2B. The VP of RevOps title has grown 300% in the past 18 months. 79% of organizations now have a formal RevOps function. But mid-market can't hire fast enough.
-
AI agents are the new category. 46% of YC's Spring 2025 batch were AI agent companies. The market is moving from "AI-assisted" to "AI-operated." Revenue operations is a perfect fit — structured data, clear success metrics, high cost of human labor.
-
CRM APIs are mature. HubSpot, Salesforce, and Zoho all have robust OAuth + webhook APIs. The integration layer that would have taken 2 years in 2018 takes 2 months now.
| Size | How We Calculate | |
|---|---|---|
| TAM | $8.5B | RevOps platform market by 2030 (17.3% CAGR from $3.65B in 2023) |
| SAM | $2.1B | Mid-market B2B SaaS companies (50-500 employees) with CRM — ~42K companies x $50K ACV |
| SOM | $210M | 10% of SAM — achievable with product-led growth + mid-market sales motion |
Adjacent expansion:
- AI agents market growing at 45.8% CAGR to $50.3B by 2030
- 96% of revenue leaders expect AI tool usage by end of 2026
- Only 52% of mid-market companies have RevOps today vs 84% enterprise — massive whitespace
| Plan | Price | Target | Deals |
|---|---|---|---|
| Free | $0 | Try-before-buy | 20 deals, rule-based agents |
| Starter | $499/mo | Small teams | 250 deals, LLM agents, Chat, Slack |
| Growth | $1,499/mo | Scaling teams | 1,500 deals, Forecast, Learning Loop |
| Pro | $3,500/mo | Mature RevOps | 5,000 deals, Autonomous Mode, SSO |
| Enterprise | Custom | Large orgs | Unlimited, Multi-CRM, BYOL, VPC |
Unit economics target:
- Blended ACV: ~$18K (weighted toward Growth/Pro)
- Gross margin: 80%+ (AI inference costs ~$50-150/mo per tenant)
- LTV/CAC target: >3x
- Net revenue retention target: >120% (seat expansion + plan upgrades)
Land and expand: Free tier builds pipeline. Convert to Starter/Growth with LLM agents. Expand to Pro with autonomous mode as trust builds.
Early access — onboarding design partners now.
What we've built (shipped, working product):
- Full product live: Dashboard, 7 AI agents, CRM sync, Gmail integration, Chat, CRO Brief, Forecast
- 33 database tables powering a complete RevOps data model
- 22 API route modules — deals, risk, forecast, actions, billing, SCIM, webhooks, team, roles
- 4 CRM integrations: HubSpot, Salesforce, Zoho CRM, Gmail
- Learning Loop: Self-improving system — rep bias detection, stage win rate calibration, forecast drift alerts, Brier score tracking
- Autonomous Mode: 3-gate safety (field allowlist + safety score + rollback with pre-apply snapshots)
- Multi-tenant: Full RBAC, custom roles, team invites, SCIM provisioning
- Stripe billing: Plans, checkout, trials, portal — all wired up
- Admin + Super Admin: Agent performance monitoring, audit logs, cost tracking
- i18n: 4 languages (EN, DE, FR, IT)
What the product does in production:
- Connects to CRM via OAuth in under 5 minutes
- Runs daily risk scans across entire pipeline
- Generates per-deal risk scores with factor breakdowns
- Drafts follow-up emails and hygiene fixes for human approval
- Delivers weekly CRO briefs with pipeline analysis
- AI-adjusted forecasts with confidence intervals and bias detection
- Chat interface for natural language pipeline queries
Autonomous Actions | Manual / Advisory Only
|
Full Suite RevAgent | Clari ($2.6B)
(Risk + Pro/Enterprise | Gong ($7.25B)
Forecast + |
Hygiene + --------------------|--------------------
Follow-up + |
Brief) RevAgent | BoostUp
Starter/Growth | Aviso
|
Point (no one here - | Scratchpad (CRM only)
Solution point solutions | People.ai (activity only)
don't automate) | Revenue.io (calls only)
Why we win:
| RevAgent | Clari | Gong | Scratchpad | |
|---|---|---|---|---|
| Risk scoring | Per-deal, daily, AI | Pipeline-level | No | No |
| CRM hygiene | Auto-fix suggestions | No | No | Manual |
| Follow-up drafts | AI-generated, Gmail send | No | Templates | No |
| Forecast | AI-adjusted + bias detection | Yes | Yes | No |
| CRO Brief | Automated weekly | Manual | No | No |
| Autonomous mode | Yes, with safety gates | No | No | No |
| Pricing | $499-3,500/mo | $100K+/yr | $250/user/mo | $49/user/mo |
| Target | Mid-market | Enterprise | Enterprise | SMB |
Our wedge: Mid-market companies can't afford Clari + Gong ($200K+/yr combined). They need one tool that does risk, hygiene, follow-ups, forecasting, and briefing — and actually takes action. That's RevAgent.
Abhishek Chauhan — Solo Founder & CTO
- Senior AI Engineer, 8+ years software engineering, 2+ years building production-grade agentic systems
- Expert in LangGraph multi-agent architectures, RAG/GraphRAG pipelines, scalable LLM infrastructure (vLLM, Ollama)
- Built LangGraph multi-agent systems serving 10,000+ users at FRACTZ (Florence, Italy)
- Generated 1M EUR revenue through intelligent automation at GB Viaggi (Milan)
- Deployed GPU inference stacks handling 100K+ daily requests on GCP
- 3x startup founder: DeCellar (3-year profitable exit, NFT wine marketplace), Invebit (Bitcoin wallet), FiGo (AI fitness marketplace)
- Full-stack: Python, TypeScript, Next.js, Supabase, GCP, AWS, Kubernetes, Solidity
- BSc Information Technology (First Class Honours), University of Hertfordshire
- Google Cloud certified (GKE, Compute Engine, Microservices)
What I've shipped (solo):
- Complete product: 7 AI agents, 33-table data model, 22 API modules, 4 CRM integrations, Stripe billing, multi-tenant RBAC
- Entire stack built and hardened — production-ready codebase with comprehensive security audit completed
- github.com/ac12644 | linkedin.com/in/ac12644 | abhishekchauhan.it
Raising:
Use of funds:
- 50% — Go-to-market: First 5 design partners, product-led growth, content marketing targeting mid-market RevOps
- 30% — Engineering: Salesforce deep integration, advanced Learning Loop, custom agent builder
- 20% — Operations: SOC 2 Type II certification, infrastructure scaling, first GTM hire
Milestones to hit in 12 months:
- 10 paying customers (Growth+ tier)
- $150K ARR
- <5% monthly logo churn
- Net revenue retention >110%
- SOC 2 Type II certified
Today: AI RevOps analyst for mid-market B2B SaaS. Year 2: Expand to all B2B verticals (services, manufacturing, healthcare IT). Year 3: Platform play — custom agent builder, marketplace for industry-specific agents. Long-term: The autonomous revenue operating system. Every B2B company has a RevAgent running their pipeline.
The $8.5B RevOps market is moving from tools to operators. We're building the operator.
+------------------+ +------------------+ +------------------+
| Next.js 16 | | Hono API | | AI Agents |
| App Router |---->| 22 route |---->| LangGraph + |
| shadcn/ui | | modules | | GPT-4o-mini |
| Tailwind | | Drizzle ORM | | 7 agents |
+------------------+ +------------------+ +------------------+
| |
+------v-------------------------v------+
| Supabase Postgres |
| 33 tables · Auth · Realtime · Cron |
+---------------------------------------+
| |
+-----------+---+ +-------+--------+
| CRM APIs | | Gmail OAuth |
| HubSpot | | Send/Read |
| Salesforce | +----------------+
| Zoho CRM |
+---------------+
Stack: Next.js 16, Hono, Supabase (Postgres + Auth + Realtime), Drizzle ORM, LangGraph, OpenAI GPT-4o-mini, Stripe, Vercel
- Evaluates every deal against 10+ risk factors: stale close date, missing next step, stuck stage, declining engagement, budget uncertainty, champion departure, competitive pressure
- Outputs a 0-100 risk score with factor-by-factor breakdown
- Triggers escalation when score exceeds configurable threshold (default: 70%)
- Self-calibrates via Brier score tracking and risk calibration samples
- Compares raw CRM pipeline roll-up against AI-adjusted forecast
- Applies stage-specific win rate priors learned from historical outcomes
- Detects rep-level bias (optimistic/pessimistic patterns)
- Outputs confidence intervals and revenue confidence index
- Tracks forecast accuracy over time (MAE scoring)
- Rep bias detection: Identifies reps who consistently over/under-forecast
- Stage win rate calibration: Updates Bayesian priors on stage-to-close conversion rates
- Drift detection: Alerts when pipeline behavior diverges from historical patterns
- Feature importance tracking: Identifies which risk factors are most predictive
- Brier score calibration: Measures probabilistic forecast quality over time
- Detects CRM data issues: overdue close dates, stuck stages, missing fields, inconsistent data
- Generates specific fix suggestions (new close date, correct stage, next step text)
- In autonomous mode: applies fixes directly to CRM with rollback snapshots
- Identifies deals that need outreach based on engagement signals
- Drafts personalized emails using deal context, risk factors, and activity history
- Sends via Gmail OAuth on approval
- Configurable follow-up thresholds
- Weekly executive summary delivered via email
- Highlights: slipping deals, hidden risk, recommended interventions, forecast changes
- Downloadable as markdown or board pack format
- Covers pipeline health, risk distribution, and action items
- Natural language interface to pipeline data
- Answers questions like "Which deals are most at risk?" or "What's our forecast for Q2?"
- Uses tool-calling to query deals, risk signals, and forecasts in real-time
- RevOps platform market: $3.65B (2023) → $10.25B (2033), 17.3% CAGR — Future Market Insights
- AI agents market: $5.4B (2024) → $50.3B (2030), 45.8% CAGR — Warmly/multiple analysts
- 93% of sales orgs cannot achieve 90%+ forecast accuracy — 310 Creative
- CRM data decays 22-70% annually — Landbase
- Sales reps sell only 2 hrs/day, 70% time wasted — Salesforce, Clari
- Mid-market RevOps adoption: 52% vs 84% enterprise — Qwilr
- Revenue leakage: 7-10% of annual revenue for B2B — Gartner 2024
- Clari: $2.6B valuation, acquired Salesloft for $1.1B (Aug 2025)
- Gong: $7.25B valuation, $300M+ ARR (Jan 2025)
- Clay: $3.1B valuation, $100M revenue expected (2025)
- 79% of organizations have formal RevOps function — QuotaPath
- VP of RevOps title growth: 300% in 18 months — Multiple sources
- 46% of YC Spring 2025 batch were AI agent companies — PitchBook