Your HubSpot Already Has AI.
We make sure it actually works.
HubSpot Elite Partner HubSpotships20+AIagentswithProfessionalandEnterpriseplans.
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Our Process
Six phases to measurable outcomes.
Discovery & Readiness Audit
Assess your HubSpot environment to determine what's possible and what needs to happen first. Evaluate plan allocation, audit CRM data quality, map workflows, and model credit consumption.
Prioritized implementation roadmap with projected ROI and credit budget model.
Data Foundation
Ensure your CRM and knowledge base are ready. Clean duplicates, standardize properties, enable data enrichment, audit knowledge base articles, and remove conflicting content.
Clean, structured data environment that agents can reliably reference.
Agent Configuration
Configure identity and brand voice, write custom system prompts, connect content sources, define escalation rules, set guardrails, and assign agents to channels.
Fully configured agents ready for testing, with documentation of all settings.
Testing & Validation
Run agents through comprehensive testing — routine questions, edge cases, out-of-scope queries, adversarial prompts, and multi-turn conversations.
Test results report with resolution rate benchmarks and refinements.
Controlled Launch
Deploy to a single channel first. Monitor in real-time for 48 hours. Track resolution rates, escalation frequency, satisfaction, and credit consumption.
Live agent deployment with baseline performance metrics.
Optimization & Handoff
Weekly performance reviews for 30 days. Refine prompts, train your team on monitoring, and create a runbook your team can follow independently.
Fully operational AI agent ecosystem with maintenance playbook.
Agents We Implement
Powered by
20+ native agents. Configured to perform.
AI front-office concierge. Resolves conversations autonomously across chat, email, WhatsApp, SMS, and more.
50%+ resolution rateAI sales development rep. Monitors leads, researches accounts, analyzes buyer signals, and drafts personalized outreach.
15 hrs/week saved per repIdentifies and fills gaps in customer data. Researches custom questions against CRM records and web sources.
Automated enrichmentGenerates blog posts, landing pages, case studies aligned with your brand voice. Repurposes existing content.
Multi-format outputTransforms content into platform-optimized social posts.
Detailed background intelligence before outreach.
Structured notes and follow-ups from call transcripts.
Patterns in lost deals with actionable recommendations.
Auto-generates docs from closed support tickets.
Smooth account transfers using CRM data.
Identifies expansion opportunities in existing accounts.
Monitors health scores and surfaces at-risk accounts.
Plus RFP Agent, ABM Landing Page Agent, Closing Agent, and custom Breeze Studio assistants.
Frequently Asked Questions
What data quality do we need before starting?
Most companies think they're ready when they're not. Three prerequisites: (1) clean contact/company records with no duplicates and standardized properties, (2) an organized, current knowledge base free of conflicting information, and (3) standardized workflows with clear lifecycle stages and escalation rules. If your CRM data is fragmented, agents will hallucinate or give inaccurate responses. Our Data Foundation phase (2–3 weeks) ensures your environment is AI-ready — this is the most critical phase for success.
How much does this actually cost once we factor in credits?
HubSpot uses a credit system that catches teams off-guard. Professional plans include ~3,000 credits/month; each Customer Agent conversation uses ~100 credits — so you get roughly 30 conversations before overage kicks in at $0.01/credit. All agents pull from one shared credit pool with no granular budgeting. We build a credit consumption model during Discovery so you understand realistic costs before launch, and optimize prompts to reduce unnecessary credit burn.
Can we customize agents to match our process, or are we stuck with defaults?
Honest answer: you get system-prompt-level customization, not workflow-level customization. You can write custom system prompts for brand voice and decision logic, define escalation rules, connect specific knowledge base sections, and set guardrails. You cannot modify the underlying agent logic, reorder input/output fields, or integrate external tools beyond HubSpot workflows. If your process doesn't align with a pre-built agent design, we assess whether custom assistants in Breeze Studio are the better fit.
What resolution rates should we actually expect?
Resolution rate is industry-dependent: 50–70% is excellent for customer support, 80%+ for routine inquiries (billing, password resets), and 10–30% for complex issues that need human judgment. Initial rates often land at 30–40% — that usually means an incomplete knowledge base, not a broken agent. Real example: Kaplan Early Learning reached 37% autonomous chat resolution within 3 months. We target 50–60% on the Customer Agent within 8 weeks, with ongoing optimization to improve from there.
What happens when agents make mistakes or give wrong answers?
This is the most important implementation question. Our Testing & Validation phase includes adversarial testing — we intentionally try to break agents with edge cases and out-of-scope questions. Post-launch, every agent decision is logged in an audit trail so you can trace exactly why it did something. We provide 30 days of active monitoring and a runbook your team can follow independently. The real risk isn't occasional mistakes — it's turning agents on and ignoring them for two months.
How long does implementation take, and what's our time commitment?
Our six-phase methodology runs 6–8 weeks: Discovery (1–2 wk), Data Foundation (2–3 wk), Configuration (1–2 wk), Testing (1 wk), Controlled Launch (1 wk), Optimization (4 wk). Your time commitment: 4–5 hours/week during early phases, 2–3 hours during testing, and 5–10 hours/week during launch monitoring. After handoff, your team manages agents independently with our runbook.