How is your AI different from just using ChatGPT or HubSpot AI?

We fuse AI models with our proprietary GTM frameworks, RevOps KPIs, and competitive playbooks. It is not a chatbot, it is an execution system that runs inside HubSpot.

Do I need to be technical to use this?

No. ARISE OS is delivered through dashboards, workflows, and custom UI cards. You act on insights, not code.

What if I do not want full AI control?

You do not have to. Everything is configurable. We deploy inside your HubSpot portal—your data, your rules.

Deploy a HubSpot native AI-BDR

Deploy a custom AI-BDR for your revenue team that synthesises the signals you choose, how you choose and produces personalised emails at scale.

Book an AI BDR Call →

The AI Prospecting Layer: Intelligent Outbound at Scale

Most prospecting automation sends the same templated email to everyone. ARISE GTM's AI Prospecting Layer calculates what problems each target company faces, then personalises how you communicate based on persona and context.

How It Works (Top-Line):

Step 1: Intelligence Gathering

AI workflows pull company data (firmographics, technographics, hiring signals) and synthesise it with your GTM Strategy object to understand:

What GTM problems this company likely faces
Which of your value propositions maps to their situation
What proof points would resonate based on similar customers

Step 2: Persona-Specific Communication

The layer applies MEDDIC + your value proposition to determine:

How each persona expects to be reached (diagnostic email for VP/Heads, strategic for CXOs)
What messaging angle fits their role and context
Which content assets prove your expertise for their specific challenge

Step 3: Scoring & Prioritisation

Every prospect gets scored: Hot, Warm, or Nurture based on:

ICP fit against GTM Strategy criteria
Timing signals (hiring, funding, tech stack changes)
Content readiness (does marketing have the assets to support this play?)

Step 4: Content Strategy Alignment

AI analyses your existing content library and:

Identifies gaps (you're targeting this ICP but lack proof point content)
Suggests new content with SEO strategy to fill gaps
Aligns sales outbound with marketing content calendar

Result: Sales and marketing operate from the same intelligence. ABM strategy writes itself.

The Methodology:

This isn't a feature. It's a framework. The AI Prospecting Layer uses native HubSpot properties, custom properties, and related objects to build executable outbound strategy that scales without losing personalisation.

Token Budget Management + Best Practice Governance

AI workflows cost money. Every API call to OpenAI, Claude, or other LLMs consumes tokens. Without governance, costs spiral, and ROI disappears.

How ARISE OS Manages AI Spend:

Token Usage Calculation

Every AI-powered workflow calculates token consumption before execution:

Competitive intelligence enrichment: ~2,000 tokens per company
Personalised email generation: ~800 tokens per prospect
Strategy synthesis: ~5,000 tokens per GTM Strategy record

We show you exactly what each workflow costs and let you set budgets by workflow type.

Best Practice Governance

Workflow-Level Controls:

Set maximum token spend per day/week/month per workflow
Prioritise high-value workflows (hot prospects get AI personalisation, nurture gets templates)
Auto-pause workflows that exceed budget thresholds

Optimisation Built In:

Caching for repeated queries (don't re-analyse the same competitor 50 times)
Batch processing where possible (analyze 10 prospects in one call vs 10 separate calls)
Smart triggers (only run enrichment when new data appears, not on every record update)

Transparency: Monthly reporting shows:

Token consumption by workflow type
Cost per outcome (cost per competitive intel record, cost per personalized email sent)
ROI analysis (token spend vs pipeline generated, deals closed, expansion revenue)

The Result:

You know exactly what AI costs, what it produces, and whether it's worth it. No surprise bills. No runaway spend. Just intelligent resource allocation.

Frequently Asked Questions

How is this different from HubSpot's AI features or other AI tools?

HubSpot's Breeze AI and other tools provide suggestions and content assistance. ARISE OS embeds AI into custom objects that execute workflows autonomously. The difference: features suggest, objects execute.

Do I need HubSpot Enterprise for this?

In some part, yes. ARISE OS works on HubSpot Professional. We use a sophisticated workflow architecture and MCP connections that operate within Professional-tier capabilities; however, custom objects require at least one enterprise seat.

What's Model Context Protocol (MCP) and why does it matter?

MCP is an open standard (developed by Anthropic, adopted by HubSpot) that enables AI workflows to access data across systems through a standardised interface. It eliminates custom integrations, reduces complexity, and enables cross-system intelligence that creates a competitive advantage.

How do you control AI costs?

Every AI workflow calculates token consumption. We set budgets at the workflow level, prioritise high-value use cases, implement caching and batch processing, and provide monthly reporting showing cost per outcome and ROI by workflow type.

Can you integrate with systems beyond HubSpot and Customer.io?

Yes. MCP enables connections to any system with an MCP server (growing list) or standard APIs. Common integrations: Salesforce, Apollo.io, LinkedIn Sales Navigator, Gong, Outreach, Salesloft and SEMRush.

How long until we see results?

AI-powered competitive intelligence is active by week 2. AI Prospecting Layer operational by week 4. Full intelligent object execution by week 6. Performance optimisation is ongoing from month 2 forward.

What if our GTM strategy isn't documented?

We help you build it. Part of our deployment process includes GTM Strategy workshops that codify your positioning, messaging, value props, and persona communication into executable Strategy objects.

Do we need technical resources to manage this?

No. ARISE OS runs on HubSpot workflows you control. We provide training, documentation, and ongoing optimisation. Your team operates the system, we ensure it stays intelligent. An annual support contract is required.

How do you ensure data security with MCP connections?

All MCP connections use OAuth 2.0 authentication, encrypted data transmission (TLS 1.3), and scoped permissions (you control what data each workflow can access). We're SOC-2 compliant and maintain enterprise-grade security across all implementations.

What happens when HubSpot or OpenAI changes their platforms?

We monitor platform changes and proactively update workflows. Because we use open standards (MCP) and a modular architecture, platform changes rarely require rebuilding; only configuration updates are needed. This is why you will need an annual support contract.