Scale Your Revenue Engine
On-demand AI engineering team to build custom GTM infrastructure.
From autonomous research agents to predictive workflows.
You describe the problem. We build the infrastructure and deploy it in your stack.
30 minutes. No product tour. Bring a problem or a vision.
Every revenue team runs differently.
You’ve invested years building a team, a process, a playbook tuned to your market. The AI layer should reflect that investment, and take it further than your current stack can.
A video streaming platform wanted to find prospects who were already talking about streaming online.
We built a system that monitors LinkedIn for specific keywords, checks firmographics, and alerts reps in Slack.
A speech AI startup needed cold outreach that didn’t sound cold.
We built a research pipeline that finds hiring signals, pulls competitor intel and recent news, and generates ice-breakers tailored to each prospect.
A global communications company had more inbound leads than their team could qualify.
We built a qualification engine that scores and routes leads in real-time. 85% automated. 3x conversion.
What’s yours?
Every team has a bottleneck or an idea they haven’t had the engineering to act on. That’s where we start.
How We Work
Discovery
We map your current process end to end. Your tools, your data, your team’s workflow, where things slow down, what your team wishes worked differently. We don’t build until we understand how you operate.
Architecture
We design the system across your existing stack. Data flows, integration points, automation logic, guardrails, escalation paths. Every decision is documented. Nothing is a black box.
Build
We build and deploy the system in your environment. Tested against your real data, integrated with your actual tools. Live in 2–4 weeks.
Optimize
The system improves over time. We tune based on real outcomes, expand to adjacent use cases, and adjust as your team’s confidence grows. Ongoing support, not a handoff.
Under the hood
Every system we build is different. Here’s the engineering toolkit we draw from.
Multi-agent systems
Specialized AI agents that handle different parts of the workflow, coordinated as one system.
Custom model training
Models fine-tuned on your data to match your brand voice, email tone, qualification criteria, or whatever else needs to sound like your team wrote it.
Vector knowledge bases
Your playbooks, product docs, competitor intel, pricing guides, structured so AI agents can query them in real time.
Memory across interactions
Context that carries over. Past conversations, stated preferences, objections, timelines, retained across every touchpoint.
Custom tool integrations
AI that calls your tools. CRM updates, enrichment lookups, Slack notifications, email sends, calendar bookings, triggered by logic you define.
Deep research pipelines
Agents that pull from company websites, LinkedIn, job postings, news, and public signals to build context on any prospect or account.
Guardrails and compliance
Every AI action runs through rules built for your business: tone, accuracy, brand guidelines, compliance requirements.
Reinforcement learning
The system improves over time. Human feedback, outcome data, and interaction patterns feed back into the AI layer automatically.
Previously built AI sales infrastructure at Twilio
Took inbound lead automation from 5% to 85%. 3x improvement in conversion rates. Deployed across 80+ countries. The same engineering approach, now available to your team.
Questions
An AI engineering company that builds custom systems for sales and revenue teams. You describe the problem, we build the infrastructure and deploy it in your stack.
No. There’s no platform to sign up for and no software to license. Every system we build is engineered from scratch for your team, your tools, and your process.
Tools like Outreach, Salesloft, or Qualified are products you configure. We’re engineers you hire to build something those products can’t. A system designed around how your team actually works, connected across your entire stack.
Four phases. Discovery: we map your process and stack. Architecture: we design the system. Build: we deploy it in your environment, usually in 2–4 weeks. Optimize: we tune based on real outcomes and expand to new use cases.
Whatever you’re already using. HubSpot, Salesforce, Apollo, Slack, Outreach, ZoomInfo, Clearbit, customer.io. We integrate with your existing stack, not replace it.
Scoped to complexity. Typically an implementation fee plus a monthly retainer for optimization and support. This is dedicated engineering, not a per-seat subscription.
Most systems are live in 2–4 weeks. First week is discovery and architecture. Remaining weeks are build and testing.
There’s something you’ve wanted to build.
30 minutes. Bring the problem or the vision. We’ll figure out the system together.
Free consultation. No commitment.