What AI tools do you use?

We build on top of the tools you already have - HubSpot, Salesforce, n8n, Make - and layer in AI from OpenAI, Anthropic, and others where it makes sense. No proprietary platform, no new vendor to manage.

Is this actual AI or just rule-based automation?

Both, depending on the job. Simple routing and alerts are rule-based - that's the right tool for that. Scoring, summarization, intent detection, and research use real LLMs. We match the approach to the problem.

Do I need to replace my CRM?

No. We build on top of what you have. Whether that's HubSpot, Salesforce, or something else, we connect to it - we don't replace it.

Do I need a technical team to manage this?

No. The automations run on their own. We build it, hand it off, and your team uses the outputs - alerts, scores, summaries - without touching the infrastructure.

How do you handle our data?

Your data stays in your stack. We don't store it, sell it, or route it through proprietary systems. The pipelines we build connect your existing tools directly.

What does onboarding actually look like?

A 30-minute discovery call, then we scope the work and send a proposal. Once you're in, we go heads-down - no lengthy kickoffs or status meetings. You see working software fast.

What if the AI gets it wrong?

It will sometimes, especially early. That's why we build human review steps where it matters and tune based on your data. Accuracy improves over time - it's not set-and-forget.

How is this different from HubSpot's or Salesforce's native AI?

Native AI works within the walls of that one tool. We connect your entire stack and build logic that runs across it - enrichment, scoring, alerts, and summaries that pull from multiple sources and trigger actions anywhere.

Claude vs ChatGPT for Sales Workflows: Which One Actually Fits?

Every sales ops person trying to build AI into their workflow eventually hits the same question: Claude or ChatGPT? Both are capable. Both are getting better every few months. And the honest answer is that the choice matters less than how you’re using it - but there are real differences worth understanding before you commit.

What each model is actually good at

ChatGPT - particularly GPT-4o - is strong at general-purpose tasks, has a massive plugin ecosystem, and is what most people have already tried. It handles email drafting, summarization, and basic research well. The integrations are mature: you can connect it to HubSpot, Salesforce, Slack, and dozens of other tools through Zapier, Make, or direct API.

Claude - particularly Claude 3.5 Sonnet and above - has a longer context window, handles nuanced instruction-following better, and tends to produce more structured output when you give it complex instructions. It’s less prone to confident hallucination on factual questions, which matters when you’re asking it to reason about deal data or customer history.

For sales workflows specifically: Claude handles long documents better. If you’re feeding it a 90-minute Gong transcript and asking it to extract MEDDIC fields, Claude will track more of it accurately. ChatGPT is better if you need to chain tools together through the ChatGPT interface and don’t want to touch an API.

Where ChatGPT has the edge

The plugin and GPT ecosystem is real. If your team wants to use an AI assistant through a chat interface without building anything, ChatGPT’s marketplace has pre-built connectors for a lot of sales tools. It’s also what most of your reps have already used personally, so the learning curve is lower.

For lightweight use - writing prospecting emails, summarizing a company’s 10-K before a call, generating objection responses - ChatGPT is fine. The gap between models at that level of task is small.

Where Claude has the edge

Long-context reasoning. If your workflow involves reading full call transcripts, long email threads, or multi-page deal summaries and extracting structured data from them, Claude performs more consistently. It also follows multi-step system prompts more reliably, which matters when you’re building agents rather than chatting.

Claude also tends to refuse less. GPT-4 can be overly cautious with sales content - emails that sound too direct, scripts that feel too aggressive. Claude handles that more pragmatically.

The question that actually matters

Neither Claude nor ChatGPT is a sales operations platform. They’re reasoning engines. The question isn’t which model is better - it’s where in your workflow you need AI reasoning, and how that connects to the tools your team actually uses.

If you’re building a pre-call brief agent that pulls from HubSpot, runs through Claude, and posts to Slack - Claude is a better fit for the reasoning step. If you want your reps to have a chat interface they can use ad-hoc without any setup - ChatGPT wins on familiarity.

Most mature AI sales stacks end up using both. Claude for backend workflows and structured extraction. ChatGPT for rep-facing, ad-hoc use. The model decision is downstream of the architecture decision.

The real mistake is treating this as an either/or when you should be asking what job you need done and which tool fits that job. Pick the one that connects to your stack, handles your use case, and that your team will actually use. Then build something.