Discover the key takeaways from Demo Day #2 featuring FullEnrich and TamTam MCPs. Learn how SDR teams leverage AI, data enrichment, and smart signals to boost sales pipeline and quota attainment.
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On 22 October, Stakki and the SDR Leaders of EMEA community ran our second vendor Demo Day. Same format as the first: two vendors, 20 minutes each, live demos, no slideware. This time the theme was the one we hear about every week: MCPs, and how to put contact data and enrichment directly into the AI tools your team already uses.
Why those topics? Dave and I went through everything the community asked about over the past year. Enrichment and AI assistants topped the list, and FullEnrich was one of the most asked-about tools. If you missed it, the full recording is on YouTube. Here's what you need to know:
The more AI use cases an SDR team runs, the more likely it is to hit target.
Dave opened with fresh data from the SDR Leaders of EMEA global State of Sales Development survey, released the same week. New tech usually takes around 18 months to cross from the US to EMEA. This time, US teams have already done the testing, trialling and auditing, so EMEA is skipping straight to real adoption.
Two findings stood out:
The use cases most linked to attainment were intent monitoring, data review, list building and account research. That's exactly the ground both demos covered. If you're heading into year end and new budget cycles, this is where to look first.
One connection gives Claude access to 20+ premium data providers in a waterfall.
Nylan leads AI operations in FullEnrich's product team. His summary of the product: there are a lot of data providers, and no single one is best for every use case. FullEnrich aggregates 20+ premium providers in a waterfall. If the first provider doesn't return the number with the best deliverability, it keeps going down the list until it finds one. Customers include Aircall, MongoDB and Strapi.
The MCP is the connector that lets your AI assistant use FullEnrich directly. It's live in Claude, ChatGPT, Grok, Microsoft Copilot, Gemini, Manus and Cursor, with Salesforce and HubSpot on the way.
Setup takes about a minute:
Why Claude Cowork, not Claude chat? Nylan said more than 50% of FullEnrich's MCP users now come through Claude Cowork. It's better at orchestrating several connectors at once, say HubSpot, Notion and FullEnrich in one task. For technical teams using Claude Code, Codex or Cursor, FullEnrich offers a CLI with an API key for the same jobs at scale.
Worried about credits? The MCP is built to ask before it spends. In the demo, Claude asked to confirm 110 credits, plus the outreach angle and tone, before running anything.
Nylan showed four jobs, each starting from a single plain-English prompt.
The prompt was simple: "Find 10 heads of sales in San Francisco at B2B tech companies with fewer than 50 employees. Find their email and phone, and create an outreach sequence for LinkedIn and email."
Claude ran a search preview, confirmed the leads matched the ICP, enriched emails and mobiles into a table, then wrote a personalised sequence for each person. The personalisation works because FullEnrich returns far more than contact details. Job title, job history, profile summary and education all come through, so Claude has real material to write from.
With a HubSpot or Salesforce connector also in Claude, you can finish the job in the same chat. The prompt users run most: "Check this list against my HubSpot. Add the people we don't already have, and leave the rest." Every lead enriched in Claude also lands in your FullEnrich account, so nothing gets lost.
Give Claude the profile of someone you've sold to many times. It uses FullEnrich to find people with a similar title, experience and background, in similar companies and the same geography. Nylan's example started from one head of sales and returned five lookalikes to target.
This is the one AEs will like. You've been handed a big account and don't know who to sell to. Give Claude the company URL and a line on what you sell, and ask it to map the buying group.
In the demo, Claude mapped the organisation from the CEO through procurement, marketing ops and the revenue team, down to individual SDRs. It scored each contact, explained why they mattered, enriched emails and mobiles, and drafted personalised first messages. With a Figma connector, it also drew the org chart.
Bonus: Sales Navigator, the browser way. FullEnrich had to remove its Chrome extension. Nylan's workaround: connect Claude to your browser and share your Sales Navigator screen. With FullEnrich connected, Claude can enrich what's on the page, much like the old extension did.
From the Q&A: "How did you get my number?" FullEnrich has a data processing agreement and an opt-out form. If a prospect objects, send them that and they can remove themselves from the database.
TamTam pairs fresh contact data with an intelligence layer of signals, scoring and context.
Eduoard, TamTam's co-founder, spent ten years in mid-market and enterprise sales before starting the company three years ago. The team is 20 people with 100+ corporate customers and 1,000+ users. He described TamTam as a "GTM harness": the same idea as Claude Code, built for go-to-market. It collects fresh company and contact data rather than reselling a static database, then layers agents on top for scoring, signals, briefs and messaging.
Eduoard's demo prompt: "Find companies in the UK hiring enterprise SDRs who use Salesforce. Sort the best 20 by employee count." His point was that not all signals are equal. A funding round is a weak one. Stronger examples he uses:
TamTam searches every variant of a title across languages: CEO, Chief Executive Officer, Directeur Général and so on. One customer booked an opportunity at Lego with a contact whose title was in Danish, someone a standard search would have missed. Eduoard said 80% of TamTam clients no longer use Sales Navigator for search.
TamTam buys from waterfall and direct providers, then adds multi-step validation. Some numbers are marked verified: confirmed as a mobile, active, and tied to that person at that company. Eduoard put it plainly: SDRs dialling bad numbers lose heart fast.
TamTam doesn't mind which surface you use: the MCP, its own UI, or Slack. In Slack, he asked for UK lookalikes of Walmart. The agent weighs context, not just firmographics, and returns a short list of real fits rather than a long one. For org charts, he prefers TamTam's live, collaborative UI, which overlays engagement from your connected LinkedIn, mailbox and CRM.
Other highlights:
The MCP isn't the hard part. The data, the context and the process behind it are.
Eduoard said it best: an MCP is only as good as the data, insight and context behind it. Both demos looked effortless because the plumbing underneath was solid. Here's how we'd act on what we saw.
Both vendors offered free credits, so you can try this before you take it to RevOps.
Burn through the credits, build a real list, then take it to your RevOps team and show them what your SDRs could do with the right tools.
Thanks to Nylan and Edward for two sharp demos, and to Dave and the SDR Leaders of EMEA community for co-hosting. Questions about anything you saw? Ask us, that's what Stakki is for.
James Donaldson
Founder, Stakki
📧 james@stakki.io
