Building Atrium: Inside the Product & Go-to-Market Journey of an AI-Native CRM

Why Now? The Market Context

The timing for Atrium wasn’t just intuition — it’s backed by market data.

• French CRM market in 2025: €1.8 billion, part of a €15B European market.

• Growth rate: 8–12% annually, outpacing global averagesAnalyse complète march….

• SME adoption: 70% of French SMEs now use a CRM (vs. <50% five years ago).

• TPE adoption: up over 90% in five years.

• Cloud dominance: 87% of new CRM deployments are SaaSAnalyse complète march….

• AI adoption: Predictive scoring, natural language analysis, and generative content are now widely understood and expected in B2B software.

And yet, most CRMs still treat AI as optional sugar on top of a legacy architecture. That’s why you see “AI assistants” that can answer questions, but can’t take meaningful action in the product.

We saw the opportunity to design a CRM that is:

• AI-first: AI drives workflows, not just insights.

• Contextual: AI appears exactly where it’s needed.

• Actionable: AI can perform complex multi-step actions on behalf of the user.

Mitra in Action

The difference between Mitra and most CRM “assistants” is that Mitra can do the work.

Example commands:

• “Enrich all leads from last week with LinkedIn and company revenue data.”

• “Create a re-engagement campaign for deals with no activity in 30 days — email + LinkedIn steps.”

• “Build a workflow that assigns high-value leads to SDRs within 5 minutes of creation.”

• “Spin up a new AI agent that monitors competitor mentions in deal notes.”

Behind each command, Mitra:

• Knows your data context (records, lists, campaigns).

• Knows your objectives (closing deals, qualifying leads, retaining customers).

• Has the permissions to act directly in the CRM.

This turns Atrium into more than a place where work is tracked — it becomes a place where work is done.

Roadmap: Building from Foundation to Autonomy

Our roadmap is designed to ship value early while building toward a fully autonomous CRM experience.

Q3 2025 — Foundations

• Core CRM objects (contacts, companies, deals)

• AI writing assistance for emails and notes

• Record enrichment from public and proprietary sources

• Notes & comments linked to records

• Views, lists, and filters

• Initial dashboard

• Website launch for early sign-ups

Q4 2025 — Intelligence & Orchestration

• Chat Mitra (full AI-embedded interface)

• Multi-channel campaigns (email, LinkedIn, etc.)

• Retrieval-Augmented Generation (RAG) for contextual AI answers

• Notifications & settings

• First integrations (Composio, Merge)

• Early workflow builder

Q1 2026 — Autonomy & Insights

• AI actions: Mitra can trigger tasks, campaigns, and workflows without prompts

• Automations with conditional logic

• Reporting & analytics with AI-generated insights

• Full documentation for users & developers

• Bug fixes and UX polish

Q2 2026 — Optimization & Growth

• Feature performance optimization

• Onboarding and activation improvements

• GTM scale-up

From Wireframes to User Journeys

Before we wrote a line of code, we wireframed every core feature to make sure AI was contextual and actionable from day one.

Wireframe modules:

• Dashboard — A high-level AI-powered pulse on pipeline health, with Mitra able to trigger follow-ups instantly.

• Pipeline — A visual, Kanban-style board of deals by stage, enriched with AI insights. Mitra can identify at-risk opportunities, suggest actions to move deals forward, or automatically reassign stalled deals to the right owner.

• AI Actions — Prioritized suggestions from AI, each executable in one click or via Mitra.

• Emails — AI-assisted writing, personalization, and scheduling within the CRM’s inbox.

• Notes — Linked to records, auto-summarized, and convertible into tasks or campaigns via Mitra.

• Campaigns — Multi-channel campaign builder; Mitra can generate sequences from a goal description.

• Workflows — Visual automation builder powered by Reactflow; Mitra can pre-build flows based on outcomes.

• Agents — Configurable AI agents (Deal Coach, Pipeline Health, Meeting Intelligence) that can be created or tuned by Mitra.

• Records — Fully enriched profiles with live data updates.

• Lists — Dynamic segments that update in real time; Mitra can create lists based on complex conditions.

• Settings — Integration setup, AI preferences, permissions — all configurable via Mitra.

This process ensured the AI is not an afterthought — it’s designed into the workflow from the start.

We picked a modern, flexible stack that lets us ship fast and scale cleanly:

• Frontend: Next.js, Tailwind CSS, Shadcn/ui, React.js

• Backend: Fastify, tRPC, Drizzle ORM, Neon DB

• Agentic AI: Langchain, LangGraph, LangAPI, FastAPI

• Specialized Tools: Reactflow (visual flows), Resend (email automation), BetterAuth (secure authentication), Merge (Integrations), Composio (Integrations)

• Developer Experience: vite.dev for rapid iteration

Why it matters: This stack allows weekly releases, supports deep AI integration, and ensures the product remains fast as datasets grow.

Our GTM approach follows the AARRR framework:

• Acquisition — Founder-led storytelling on LinkedIn and X, partnerships with GTM consultants, educational content on AI in sales, Cold Outreach.

• Activation — Deliver the first “AI win” in under 10 minutes via onboarding flows. 40% off first 3 months.

• Retention — AI agents embedded in daily workflows so the product is habit-forming. Newsletter. Tutorials. Weekly advanced webinars, 1:1 support.

• Referral — Built-in invite rewards for early users.

• Revenue — Freemium base, premium tiers for advanced AI and automation, Tokens.

Our ICP is B2B SaaS companies with 5–50-person GTM teams — tech-forward, growth-minded, but too lean to maintain complex enterprise CRMs.

Execution: Lean, Fast, and Focused

Team structure:

• 1 AI Engineer

• 1 Frontend Engineer

• 1 Backend Engineer

• Myself — Product management, GTM, and brand

Process:

• Weekly sprints

• Daily standups

• Backlog grooming every Friday

• Linear for tracking

• Notion for documentation

We run on Agile principles to keep cycles short and learning continuous.

Lessons Learned

Design AI-first workflows — AI must be part of the process, not an extra step.

• Keep AI in context — Users shouldn’t have to “go find” the AI; it should live where they are.

• Speed matters — Shipping quickly lets us validate and adapt faster than competitors.

• Small teams can move big — With tight focus and the right stack, velocity beats headcount.

What’s Next

We’re moving into private beta with:

• Mitra live across all core modules

• Key integrations operational

• First batch of early adopters onboarded

The mission remains clear:
Make Atrium the CRM that does the work for you.