We run a four-phase programme that turns HubSpot’s AI from a switched-off feature into hours and revenue you can measure. It starts with a fixed-fee assessment — not a retainer.
Fixed fee. Two workshops. You keep the roadmap either way.
Nearly every mid-market business has now switched something on. Very few can tell you what it saved them.
The dashed line is the value that’s been paid for but not yet captured.
In a recent HubSpot partner survey, 67% of customers said they were interested in AI but cautious. That caution is rational — most AI projects stall in pilot, because the work never gets embedded into how the team actually operates.
The gap isn’t the technology. It’s the absence of a structured way to move from “we turned it on” to “it changed how we work, and here’s the number.”
Every client sits somewhere on this ladder. The job isn’t to leap to the top — it’s to prove value at your current stage, then earn the next one. The bar shows how much of the work runs without a human in the loop.
Most teams are sitting on untapped value inside HubSpot already. Embedded AI needs almost no behaviour change and no setup — it shows up in the workflows people are in every day and saves time from day one. This is where nearly everyone should begin, including teams who think they’re past it.
[Draft] Breeze assistants draft, summarise and research inside HubSpot. A person still makes every decision, but routine writing and look-ups take minutes instead of hours. The work here is building the habit across a team, not just a few enthusiasts.
[Draft] Breeze agents handle defined jobs end to end — answering tier-one tickets, researching prospects, qualifying leads — with a person reviewing exceptions rather than every step. This is where the hours start to add up, and where clean data matters most.
[Draft] Agents and integrations built around your own systems and logic, beyond what HubSpot ships. Worth it once the earlier stages are working and the data underneath them can be trusted.
Not sure which stage you’re on? That’s the first thing the assessment answers.
A cycle, not a project. Each pass through it proves a result and earns the right to take on the next piece of the business.
Two 90-minute workshops. We map your go-to-market processes end to end, audit the data and systems feeding HubSpot, and find where time is actually being lost. Then we prioritise, together, in a third session.
You get A phased roadmap, a prioritised solution plan, and the ROI case.
Clean the CRM, configure AI settings and brand voice, then ship zero-to-low-cost wins in week one. The first real workflow goes live to one team, controlled and supervised.
You get Visible time savings inside the first month.
We go back to the baseline recorded in Phase 1 and compare it against what actually happened. Hours reclaimed, tickets deflected, AI spend set against the manual labour it replaced.
You get A defensible number you can take to your board.
AI degrades quietly. Data drifts, products change, people revert to old habits. We audit transcripts, keep knowledge current, train new starters, and roll the next workflow out.
You get Systems that stay accurate as the business changes.
Long discovery phases kill momentum. Alongside the workshops we switch on low-friction wins your team feels immediately — most already included in what you pay HubSpot.
Support reps get on-brand draft replies pulled from your own knowledge base.
Call transcripts land in HubSpot, where the rest of the AI can use them.
Configured once, so every AI-generated word sounds like you rather than a chatbot.
One strong asset becomes a month of channel-appropriate posts and emails.
40+ company and contact fields auto-filled, so personalisation has something to work with.
A 28-day Customer Agent or Prospecting Agent trial, scoped to one team, at zero cost.
Start smaller. Run a free AI visibility check to see whether ChatGPT, Perplexity and Google AI Overviews mention you when buyers ask about your category.
Check my AI visibility→These five carry the most impact for mid-market teams on HubSpot. There are another twenty in the full library — we scope those during discovery.
Campaign generation, content remixing and performance analysis that compresses the time from idea to live.
Your buyers ask an AI before they ask Google. We restructure your content so it gets cited in the answer.
[Draft] An agent builds the account brief, finds the right contacts and drafts a first touch, so reps spend their time on conversations.
[Draft] Calls are summarised, next steps logged and follow-ups drafted automatically, so nothing waits for a rep to catch up on admin.
[Draft] A Customer Agent resolves common questions from your own knowledge base, and hands the rest to a person with the context attached.
Three stepping stones. Most clients begin and end at step one before deciding anything else — and that’s a legitimate outcome.
A diagnostic, not a commitment. We find the low-hanging fruit, check your data is ready, and hand you a plan.
We build the top priorities from your roadmap and get the first real workflow live with one team.
For teams running AI in production. Governance, enablement, and the next workflow — every month.
We price the outcome, not the hours. You aren’t buying thirty days of consulting — you’re buying back twenty hours a week of research time, or a 15% cut in tier-one tickets.
A worked example for an SDR team of ten. We build the same five lines from your own numbers during Phase 1.
10 SDRs × 50 prospects a week × 20 minutes of research each = 167 hours a week. At €50/hour that’s roughly €33,000 a month spent on research alone.
A prospecting agent cuts research from 20 minutes to about 5 — a 75% reduction, freeing roughly 12 hours per rep per week.
2,000 prospects a month at ~100 credits each. On most plans, credits your subscription already includes but nobody is spending.
Your SDRs keep spending half their week on research while competitors reach the same buyers first, and at greater scale.
Reclaim ~€25,000/month in SDR capacity.
Same headcount, faster outreach, better personalisation.
Illustrative figures. We’re deliberately conservative when we build yours — a number you can defend beats a number that looks good.
[Draft] Most teams aren’t, and that’s fine. The assessment checks your data first, and cleaning the CRM is the first job in Activate. AI on messy data gives confident wrong answers, so we fix the foundation before anything goes live.
[Draft] Then you’ve spent a fixed fee to avoid a much bigger mistake. You keep the roadmap and the data audit, and you can act on them with us, in-house or with another partner.
[Draft] Usually not. Most week-one wins and many agent use cases run on features and credits your subscription already includes. Where an upgrade would pay for itself, the ROI case shows it.
[Draft] The aim is to take repetitive work off people, not to take people out. In most projects the hours reclaimed go back into selling, serving customers and the work the team didn’t have time for.
[Draft] Your team, with documentation and training from us. If you’d rather not, the AI operations retainer covers governance, audits and the next rollout each month.
[Draft] Week one. Quick wins go live alongside the workshops, and the first real workflow reaches one team within the first month.
A fixed-fee readiness assessment. Two workshops, a prioritised roadmap, and an ROI case you can put in front of a board. No retainer, no lock-in.
