When CRM-native AI is exactly what you need — and when the problem spans systems HubSpot can’t see.
We use HubSpot (and integrate with Breeze) on most RevOps engagements. This isn’t a hit piece — HubSpot AI is excellent at what it’s built for.
TL;DR
Use HubSpot Breeze when your AI workload lives inside HubSpot’s data layer — it’s included, well-tuned and gets better every quarter.
Build with Shakan when decisions span HubSpot plus other systems (Salesforce, billing, product, support, ops) and you need custom logic, evals in CI and orchestration across the revenue + ops layers HubSpot can’t see.
| Dimension | HubSpot AI (Breeze) | Shakan AI |
|---|---|---|
| Setup cost | Included with HubSpot subscription; zero incremental setup | $20K+ implementation, 4–10 week build, scoping and evals |
| Monthly cost | Bundled with the seat plan; predictable | $3K+ MRR retainer for ops, eval runs, model upgrades |
| Time-to-value | Minutes — features ship inside HubSpot UI | Phase 1 in 3–4 weeks; full system in 6–10 weeks |
| IP ownership | Configuration lives in HubSpot; the AI is a feature you rent | You own the code, prompts, evals, infrastructure, and escrow |
| Customisation depth | Excellent inside HubSpot's data model and surfaces | Arbitrary logic across HubSpot + Salesforce + ops systems + custom apps |
| Observability | HubSpot-native dashboards; limited trace-level visibility | LangSmith + OpenTelemetry tracing, p95 latency, cost-per-conversation |
| Evals & guardrails | Tuned by HubSpot; you don't run regression suites against it | Versioned golden datasets, regression suites in CI, schema validation, refusal patterns |
| Vendor lock-in | Tightly bound to HubSpot's data and surfaces | Portable: framework + models swappable; logic in your repo |
| Multi-system orchestration | Strong inside HubSpot; sees only what HubSpot ingests | First-class across HubSpot, Salesforce, billing, support, finance, and custom systems |
| AU compliance | HubSpot's generic data residency and controls | AU residency, AHPRA / AUSTRAC / AFSL touchpoints designed in per vertical |
| Who builds it | Your RevOps or HubSpot admin enables the features | Senior engineer ships the system end-to-end |
| What happens at scale | Feature ceiling: stops where HubSpot's data model stops | Architecture spans revenue + ops layers; absorbs scale and edge cases |
On most RevOps engagements, HubSpot stays as the system of record and Breeze keeps doing what it’s good at: drafting emails, summarising deals, suggesting content. Shakan builds around it rather than against it.
A typical pattern: a LangGraph state machine reads HubSpot contacts, joins them with product-usage data from a warehouse, billing state from Stripe, and support context from Zendesk; runs a scoring agent with eval-tested prompts; writes a structured outcome back into a HubSpot custom object that reps see in their existing UI. HubSpot is the surface; Shakan is the architecture that crosses systems.
Shakan engagements start at $20K+ for implementation and $3K+ MRR for ongoing operations.
HubSpot Breeze is bundled with your seat plan — effectively zero incremental cost. The fair comparison isn’t Breeze vs Shakan on dollars; it’s whether the AI work that Breeze cannot do is worth a dedicated build. For workloads that span HubSpot plus other systems, the answer is usually yes.
Yes, for everything it does well — email drafting, summarisation, content suggestions, prospecting inside HubSpot's data. The question isn't Breeze or Shakan; it's where Breeze stops and your business problem keeps going. We'll help you draw that line and tell you honestly when Breeze alone is enough.
Yes — and that's the most common pattern. HubSpot remains the CRM of record. Shakan builds the LangGraph-orchestrated logic that reaches into HubSpot via its API, joins it with data from Salesforce, billing, support and product analytics, makes the decision, and writes the outcome back to HubSpot as a structured record. Reps see the result where they live; engineering owns the logic where it belongs.
A versioned golden dataset per intent — say, 200 representative deal-stage transitions or 200 outbound emails per persona — regression-tested in CI on every prompt or model change. We A/B Claude Sonnet 4.6, Opus 4.7, Haiku 4.5, GPT-4o and DeepSeek-V3 on the same rubric and pick per workload. HubSpot is tuned by HubSpot; we tune for your specific outputs and revenue impact.
Breeze will keep getting better, and for HubSpot-only workloads it may genuinely close the gap. The structural gap that won't close: HubSpot AI can only reason about data inside HubSpot. If your decisions need product usage, billing state, support context or finance approvals, no roadmap fixes that. Custom architecture is the right answer when the problem lives between systems, not inside one.
Breeze is bundled with your HubSpot seats; there's no incremental dollar cost. Shakan engagements start at $20K+ implementation and $3K+ MRR. The honest comparison is total economic value: if Breeze covers 80% of your AI workload, keep it. If the missing 20% is the most expensive 20% — the revenue decisions, the cross-system orchestration, the compliance-sensitive paths — that's where custom architecture earns its keep.
45 minutes with a senior architect. We’ll map your revenue + ops stack, identify the decisions HubSpot can’t see, and tell you honestly whether custom architecture is worth the investment.