u/Impossible-Home5679

▲ 2 r/techsales+1 crossposts

Would you let someone build your "pre-CRM" layer inside your own stack instead of buying another SaaS?

Hey all — looking for honest feedback from sales leaders, especially anyone selling into professional services (law, accounting, consulting, finance, recruitment).

I've been building something, but before I push further, I want to sanity-check the delivery model, not just the features.

The problem I keep seeing:

  • Junior SDRs (1–2 yrs out of uni) are expected to sound credible to partners, GCs, directors from day one. They're not ready, confidence drops, churn follows.
  • Cold calling with no context = burnout = low volume = missed targets.
  • CRMs get polluted with thousands of "no answer" logs and unverified contacts. Forecasting becomes fiction.
  • Heads of Sales have zero clean top-of-funnel visibility.

What the workflow does:

I'm asking professionals selling to professional services specifically, or those where knowing who to call or getting their contact information is not the challenge. Take law firms, you want to speak to a corporate partner of a law firm, you can get all their direct contact info from the law firm website, the workflow starts from the assumption, that data is not the issue.

  • AI-generated call prep cards before every dial — prospect intel, company context, talking points, "why they care," suggested openers. Built from whatever LLM you already pay for (Claude / GPT / Gemini).
  • pre-CRM intelligence layer so junk never enters HubSpot/Salesforce. Smart dedupe on email + domain, conflict handling, push-to-CRM only for real conversations.
  • Bulk import / event list cleanup with ICP scoring and CRM matching at ingest.
  • Account-led SDR workflow — named accounts, work periods, multi-touch multi-person campaigns.
  • Call logging + follow-up tasks that automatically sync to CRM with a clean disposition taxonomy.
  • Leadership reporting — channel performance, best time to call, account-level insight, separated from pipeline data so forecasting actually works.

Here's the unusual part — the delivery model I want feedback on:

Instead of selling it as another SaaS subscription, the idea is: we come in, build the workflow blueprint inside your organisation, using your existing CRM and your existing LLM contract. You own it completely when we leave.

  • No ongoing licence fee
  • No per-seat SaaS pricing
  • No vendor lock-in
  • LLM-agnostic — your AI cost doesn't change
  • Your team owns and maintains it after handover

The pitch is basically: you've already paid for Claude/GPT and HubSpot — why pay a third vendor to glue them together forever, when someone can build the glue once and hand you the keys?

What I want to know:

  1. If you're a Head of Sales / CCO / RevOps lead — does "built inside your stack, you own it" actually sound better than buying another tool? Or does it sound like a maintenance headache you'd rather outsource?
  2. Is "another SaaS subscription" actually a real objection in your world right now, or am I projecting?
  3. What would make you trust a build-and-handover engagement vs. just buying Gong/Apollo/Clay/etc.?
  4. For those selling into professional services specifically — does the junior-rep-credibility-gap resonate, or is that not where the pain actually sits?

Not selling anything here, no link, no DM funnel. Genuinely trying to figure out if the model is the right shape before I commit harder.

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u/Impossible-Home5679 — 1 day ago
▲ 14 r/AI_Governance+2 crossposts

I've been deep in the EU AI Act for months now, mainly from the practical compliance side rather than pure legal theory.

The thing that keeps coming up in conversations is that most organisations can't even get past step one, building an inventory of which AI systems they actually use. Compliance teams know the deadlines exist but the gap between "we should do something" and "here's what we're actually doing" seems massive.

Curious what others are finding. If you're working on AI Act compliance in any capacity; legal, compliance, product, engineering — what's been the single biggest challenge?

A few specific things I'm wondering:

  • Is the biggest blocker understanding the regulation itself, or operationalising it?
  • Are you finding the provider vs deployer distinction straightforward or confusing in practice?
  • Has anyone actually completed a full AI inventory yet?

Genuinely interested in what the reality looks like on the ground.

reddit.com
u/Impossible-Home5679 — 13 days ago