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We just opened early access sign-ups to Qlauson — looking for MedTech, pharma, manufacturing & food production teams to shape it

Hey everyone,

I’m building Qlauson, an AI system designed for industries where recurring issues are expensive, regulated, and dangerous — especially:

  • MedTech

  • Pharma

  • Manufacturing

  • Food production

  • Industrial operations

We just opened early sign-ups for free early access.


What Qlauson does

In most operational environments, when something goes wrong:

  • a defect appears

  • an incident is logged

  • a deviation is recorded

  • an audit question comes up

The first question is always:

“Has this happened before?”

Right now, answering that takes hours or days across:

  • Jira / ticketing systems

  • CAPA systems

  • SharePoint / Confluence

  • emails

  • local files

  • and usually… asking someone who “remembers”


The problem

What we keep seeing in regulated environments:

  • recurring incidents are not recognized early

  • CAPAs are recreated instead of reused

  • audit trails are fragmented

  • root cause analysis repeats from scratch

  • knowledge is trapped in different systems

This leads to:

  • repeated failures

  • wasted investigations

  • compliance risk

  • and preventable production issues


What Qlauson is

Qlauson is an AI-powered operational memory layer that connects:

  • incidents

  • quality events

  • CAPAs

  • audits

  • documentation

And answers:

“Has this happened before — anywhere in your systems?”

It then shows:

  • similar past cases

  • root causes

  • what CAPA was used

  • whether it actually worked

  • and what should be done now


Early access (free)

We’re currently inviting early design partners from:

  • MedTech companies

  • pharmaceutical manufacturing

  • food production facilities

  • industrial manufacturing teams

  • quality / compliance / operations teams

Early access is:

  • free

  • feedback-driven

  • and directly influences product direction


What we’re looking for

We’re not just looking for users.

We’re looking for:

  • real operational pain

  • real incident history complexity

  • teams dealing with CAPA / audits / deviations

  • honest feedback on what actually helps vs what doesn’t


What you get in return

Early users will get:

  • free access during beta

  • priority feature requests

  • direct input into roadmap

  • custom integrations for your workflow if needed


If this sounds relevant

Drop a comment or message me with:

  • your industry

  • what systems you currently use (Jira, QMS, SAP, etc.)

  • and what pain you have with recurring issues or investigations

I’ll personally onboard a small number of teams first.


Final note

If your work involves regulated environments, audits, or production quality systems — this is exactly the type of feedback we’re building around.

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Qlauson
  1. 1

    Problem space is real — CAPA duplication, knowledge fragmentation, audit trail reconstruction are multi-million dollar problems in regulated industries.

    Three things to pressure-test:

    Regulatory compliance is the gate, not the marketing. Quality leaders can't deploy AI touching CAPAs without 21 CFR Part 11, EU Annex 11, GxP validation, ALCOA+ data integrity. Without these, conversation ends at "how do I validate it?" Must address Part 11 path explicitly.

    AI hallucination tolerance is zero in regulated context. Hallucinated citation = audit failure + regulatory action. Need strict provenance, auditable decision trails, conservative defaults, human-in-the-loop. Positioning should lead with trust mechanisms more than AI capabilities.

    Wrong channel for design partner recruitment. IH audience is consumer founders. Quality VPs are on LinkedIn, in RAPS communities, at industry conferences (RAPS, ISPE, Pittcon, IFT FIRST). LinkedIn outbound to Quality VPs at mid-market companies works better than tier-1. Auditor recommendations open enterprise doors.

    Existing competitors: MasterControl, Veeva QualityOne, Sparta TrackWise, ETQ Reliance, Greenlight Guru. Wedge isn't "QMS" — it's "AI cross-system memory layer connecting existing QMS to other knowledge sources." Beats "another QMS."

    Enterprise sales cycles 6-18 months, annual contracts $50-500K. Model runway explicitly.

    1. 1

      Thanks for the advise, however, our approach was not creating a RCA or CAPA tool.