AI agents that inspect every deal, score every account, and route every lead — inside your own AWS account.

An AI revenue agent is an autonomous process — not a chatbot — that reads your actual revenue data (call transcripts, emails, CRM notes, deal history) and produces an objective readout against a framework you define. Unlike static workflow automation, an agent applies judgment: it reads full context and decides what should happen, the way a smart RevOps analyst would — except it covers every deal and every account, every night.

Every night, the ARR agent reads every transcript, email, and note on your active deals — then scores each deal against your qualification methodology. It flags the gap between what the rep says in the CRM and what the transcript actually shows. One customer result: forecast accuracy within 1% of the called number.

Yes. The GRR/NRR agent replaces subjective health scores with a maturity model built from actual customer interactions — scored weekly, not quarterly. It flags churn risk months before the renewal conversation, not weeks. One customer result: lowest churn quarter on record.

Yes — agents-as-infrastructure deployed in your own AWS account. Your CRM connects via webhooks inside your VPC. The only external call is to the model API. No vendor servers sit in your data path, and your customer data never leaves your environment.

No. Every deployment runs inside your own AWS account — ECS Fargate, RDS, and Secrets Manager in your VPC. The only external call is to the Anthropic API. No Revenue-Growth.AI servers are in your data path, ever.

The infrastructure deploys in 29 minutes via one Terraform command. Full production rollout — including CRM connection and your custom scoring frameworks — typically completes in 14 days.

One-time CapEx starting at $20K per agent node, with an optional Fractional AI Engineering add-on for white-glove Go-To-Market deployment and custom playbook configuration. Ongoing infrastructure is pass-through AWS compute and Anthropic/Claude token cost only — typically ~$300/month at Series B volume. No per-task billing. No recurring license. No SaaS markup.

No — and deliberately so. It's a structured first deployment: you purchase your first agent node (one-time CapEx, from $20K), we deploy inside your AWS account in 14 days, and you spend the remainder of the 30 days running the agent's nightly readouts side-by-side against your human process. Your risk is bounded in a way no SaaS trial can match: no subscription, you own the infrastructure outright, and one command tears the whole system down.

Salesforce and HubSpot, connected via webhooks through an Application Load Balancer inside your VPC with IP allowlisting enforced.

This isn't a replacement — it removes the 30–50% of tedious, manual work your team performs today: deal inspection, health scoring, account reviews, forecast reconciliation. Your most skilled people stop doing repetitive analysis and start acting on objective, always-on readouts.

You have three options, and all of them work: your engineering team can own it like any other internal service (full infrastructure-as-code via Terraform, logs and alarms in your CloudWatch), you can leverage our Fractional AI Engineering tier for white-glove management and playbook configuration, or we can train your RevOps team to run it themselves. Want it gone? One command tears it down in ~30 minutes.