Breeze Agent Library.
Productized agents on your kernel.
For HubSpot customers ready to deploy agents on top of their kernel. Productized Breeze agents tuned to specific operational patterns — pricing reflects the per-agent value, not hours. Deploy in days, not quarters.
Breeze Agent Library is a Layer 04 service.
Every service we offer maps to one of four layers. Breeze Agent Library sits in the Agents — the layer that owns AI consulting & co-pilots.
Agents that do real work.
The Breeze Agent Library is a set of productized agents we have tuned, tested, and shipped across multiple client kernels. Each one solves a specific operational pattern: lead enrichment, deal hygiene, account research, ticket triage, content QA, sales-intel summarization.
Pricing reflects the per-agent value, not the build hours. Deployment takes days, not quarters, because the agent is already designed — we tune it against your kernel, validate it against your workflows, and turn it on. If the patterns we offer don't fit, see Custom MCP Servers and AI Maturity Program for bespoke work.
The process.
Discover · agent fit + readiness
Quick audit of your kernel. Identify which library agents would compound, which need kernel work first.
Expose · pick + scope
Choose 1–3 agents to start with. Define success criteria. Map them to specific workflows.
Wire · tune + deploy
Tune each agent against your data and voice. Validate on real cases. Deploy to the team.
Operate · monitor + expand
Weekly review of agent output. Tuning iterations. Add new agents as the team gets comfortable.
Agents working in production.
Things people ask before booking.
What agents are in the library?
The library evolves. Current patterns include lead enrichment, deal-hygiene scanners, account-research synthesis, ticket triage, content QA, and sales-intel summarization. The Diagnostic is the cleanest way to see which fit your operating reality.
How is pricing structured?
Per agent, not hourly. The pricing reflects the value the agent produces — typically tied to hours saved or work completed. Bundled discounts for multi-agent packages.
Do we need a clean HubSpot for these to work?
Yes. Agents inherit the quality of the data underneath. If your kernel is messy, we'll surface that in the readiness audit and recommend the kernel work first (HubSpot Implementation, Database Management, or Breeze Tuning).
How is this different from custom agents?
Library agents are pre-built and tuned to common patterns. Custom agents are bespoke for unique workflows. Custom MCP Servers and AI Maturity Program are the engagements for that. Most teams start with the library.
What does success look like at 90 days?
An agent in production doing measurable work, with guardrails your team can audit. On the Maturity Model this is the L3 → L4 move: the kernel work made the data trustworthy, and now agents act on it. Ninety days proves the pattern; the quarters after it scale it.
See how Breeze Agent Library fits into The Agents.
Before anyone deploys an agent, the diagnostic answers the only question that matters: is the layer underneath ready? Ninety minutes, your stack on the whiteboard, and a straight call on whether agents come next or kernel work comes first.