Welcome back to the EUVC Podcast where we dive deep into the craft of building and backing venture-scale companies in Europe.

Modern software doesn’t fail quietly.

It fails on Black Friday.It fails while the CFO is in a board meeting.It fails when your biggest customer is mid-way through a critical workflow.

And when it does, there’s one brutal reality:The data is there but nobody has time to interpret it.

Today we’re exploring one of the most under-discussed yet mission-critical parts of building modern software: reliability in production.

Joining Andreas are:

👩🏻‍💻 Pooné Mokari: CEO & Co-Founder, EwakeParis-based startup building AI agents for software production reliability, fresh off a $2M pre-seed led by Connect Ventures.

💥 Pietro Bezza — Managing Partner, Connect VenturesEurope’s most product-obsessed early-stage investors (Aikido, Typeform, TrueLayer), backing ewake as their next agentic AI investment in observability.

We unpack why observability is overdue for a rewrite, how AI agents finally provide the “reasoning layer” that logs & metrics never could, and how ewake is building a global devtools company out of Paris.

Here’s what’s covered:

* 01:12 | What ewake does — AI agents for software production reliability that reason across logs, metrics & code to cut through observability overload

* 02:32 | Why Connect backed them — trusted intros, a massive category (post-cloud, multi-$B), and founders with rare insider insight into reliability engineering

* 05:18 | The shift AI enables — from reactive data dashboards to an intelligence layer that correlates structured + unstructured data and finds root causes

* 07:48 | The hidden layers of tech — why deep, unglamorous infrastructure (observability, reliability, SRE workflows) is a massive opportunity for new entrants

* 08:52 | The wedge — LLMs as reasoning engines over infrastructure data: not more dashboards, but an operator that collaborates with engineers in critical moments

* 11:48 | Production ≠ code on your laptop — the real-world complexity: business context, urgency, multi-team coordination, and why semantic reasoning matters

* 14:38 | “Can we trust AI?” — why agentic workflows differ from ChatGPT, how ewake constrains context, guards against hallucinations & enforces “don’t know” responses

* 16:38 | Founder–market fit — living the pain at Criteo, deep SRE experience, and product instincts that made ewake’s pitch compelling pre-product

* 17:16 | Connect’s thesis — product-first founders, problem insight over pedigree, and why product is the highest leverage driver of venture-scale outcomes

* 22:31 | Product-led ≠ PLG — clarifying the difference between product-first strategy and the specific go-to-market motion of product-led growth

* 26:02 | How Awake raised $2M pre-product — insight clarity, storytelling from lived experience, fast-moving investors, and a clear “teammate, not dashboard” vision

* 30:40 | What Connect looks for — opinionated founders with singular insight, UX instincts, and a tinkerer’s mindset for frontier-tech categories

* 38:20 | Why build in Paris — deep AI talent pools, strong engineering culture, global problem space, and a shift toward France as a magnet for AI founders

* 42:15 | Geography myths — why great companies emerge anywhere, Europe’s deep industry advantage, and dual-hub (EU + US GTM) playbooks

* 47:23 | Where ewake is now — out of stealth, hiring, in design partnerships, building alongside early users, and stress-testing agents in real incidents

* 51:52 | Final reflections — design-led vs. tinker-led founders, why ewake fits the frontier-tech profile, and what the next wave of AI infra looks like🎧 Listen on Apple or Spotify — chapters ready to go.

✍️ Show Notes

ewake: The AI Teammate for Reliability Engineering

ewake builds AI agents that help engineers understand, diagnose, and resolve production issues faster — without drowning in dashboards.

Not another observability platform.Not another data pipeline.Not another widget to configure.

A reasoning layer.On top of Datadog, Grafana, Prometheus, Sentry, GitHub, and Slack.

The Pain Today

Software teams operate in chaos during incidents:

* Millions of logs

* Hundreds of metrics

* Dozens of dashboards

* Slack threads exploding

* Code diffs deployed minutes earlier

* Alerts half the org doesn’t understand

Everything is “visible.”Nothing is explainable.

What teams truly lack is interpretation — the meta-layer that answers:

* What actually went wrong?

* Where should I look first?

* What changed right before?

* Is this pattern anomalous?

* Who should be paged?

* Will this get worse?

ewake’s AI Agent

ewake reads all signals — logs, metrics, traces, deploy diffs, configs, threads — and reasons over them to:

* highlight root-cause candidates

* surface suspicious diffs

* cluster related anomalies

* explain issues in natural language

* summarize evolving incidents

* provide next-step suggestions

* offer context to non-engineering stakeholders

And it does this where engineers already collaborate: Slack.

“Developers don’t need more dashboards.They need a teammate that understands the data.” — Poone

This is a UX shift as big as the move from monitoring to observability — from data → reasoning.

Why Connect Ventures Backed ewake

Pietro breaks it down:

1. The intros were from world-class filters

One design-led angel + one observability founder → same intro.That’s the Connect Ventures bat-signal.

2. The market is enormous

Observability is one of enterprise AI’s largest whitespace opportunities.

3. ewake has founder-market fit

Poone and her co-founder Omid spent years on 3 a.m. on-call rotations at Criteo — one of Europe’s toughest production environments.

4. AI is the wedge incumbents can’t react to

They have the dashboards.ewake builds the intelligence layer above them.

5. A product-first, tinker-first founding style

ewake isn’t building a five-year roadmap.They’re iterating at the frontier, where models, agents, and capabilities evolve monthly.

“We overweight insight, product obsession, and problem truth over prior founder experience.” — Pietro

AI Agents ≠ ChatGPT (And Why This Matters in Production)

The #1 reliability question:“Will it hallucinate?”

ewake’s approach prevents this:

* bounded context (specific issue windows)

* deterministic workflows

* guardrails

* “I don’t know” scoring

* multi-step reasoning

* no generative fiction

ewake doesn’t build a generalist assistant.

It builds an operator.

One that can say:

“Here’s what I know. Here’s what I don’t. Here’s what you should check.”

Trust is the oxygen of reliability.

ewake’s design is built around that principle.

Why Build in Paris?

Paris has become Europe’s AI powerhouse:

* Mistral effect

* Deep ML research bench

* Top engineering schools

* A growing DevTools ecosystem

* Cross-border talent magnet

ewake is built in Paris but designed for the world.Its customers are global.Its engineering culture is global.The problem is universal.

Where ewake Is Today

ewake is:

* out of stealth

* deployed with design partners

* used internally at ewake during incidents

* iterating with human-in-the-loop feedback

* expanding agent reasoning workflows

* embedding deeper into Slack-based incident response

Their north star?

Trust.

An AI teammate that engineers actually rely on when the fire alarms go off.

💡 Investor & Founder Takeaway

ewake is building the missing layer in observability:the reasoning layer.

The shift mirrors what Copilot did for software creation — but for production operations:from “more data” → actionable, contextual intelligence.

It’s an enormous market, a painful problem, and a founding team with rare insider knowledge.

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