About

One brand for the work that still has to ship.

ScaledNative is the AI-native umbrella brand for modernization products, collaboration tooling, and the services layer that helps enterprises move from strategy to production without changing brands every time the problem changes.

The Portfolio

The portfolio is designed to be additive.

ScaledNative still carries the methodology, practitioner, and certification story. What changed is that software products now sit beside that work instead of being hidden behind a services-only narrative.

Modernization brand

DataCat

AI Data Catalyst modernization surface

Modernization

Migration platforms and governed delivery for mainframe-adjacent estates moving into AI-native execution.

DataCat, also presented on its dedicated product surface as AI Data Catalyst, leads the category with a DB2-to-PostgreSQL migration platform covering schema conversion, stored procedure translation, copybook-aware assessment, and governed validation inside the customer environment.

  • Schema, procedure, and copybook-aware migration scope
  • Runs inside the customer environment
  • Governed validation and cutover evidence

Collaboration

Agent Team Orchestration for mixed human and coding-agent delivery teams.

The collaboration pillar covers the coordination layer for lanes, handoffs, branches, reviews, and release work across human teams plus coding, QA, and release agents.

  • Message-first command center
  • Human plus agent team orchestration
  • Branch, handoff, and release visibility

Services

Embedded delivery, certification, and operating-model design around the portfolio.

ScaledNative services connect strategy to shipped systems through residencies, methodology design, and enablement led by practitioners who still build.

  • Embedded delivery residencies
  • Certification and enablement
  • Operating-model design around NATIVE

Why now.

Procurement teams are being asked to underwrite AI spend without a credible way to tell a senior practitioner from a confident one. The existing signals — conference talks, vendor certifications, LinkedIn titles — do not grade shipped artifacts. They grade narrative.

At the same time, the consultancies most enterprises default to sell slides, not shipped code. A year into the engagement there is a strategy deck, a pilot, and a new RFP. The gap between AI strategy and AI delivery has never been wider.

That is why ScaledNative is structured as an umbrella. Products where software should scale. Services where expert delivery still matters. And SNCP where the buyer needs a credible signal of who can actually be trusted in the room.

Why SNCP still matters.

The ScaledNative Certified Practitioner program is a three-tier credential — Associate, Practitioner, Master — covering seven domains of AI-native engineering, assessed through a five-stage funnel that ends in production-grade artifact review.

It is not an LMS. It is not a course library. It is a standard — written down, calibrated by people who have shipped in regulated environments, and audited by people outside the company. The curriculum and training partners exist to prepare candidates for the standard, not the other way around.

Read the full SNCP blueprint

What we do differently.

Four commitments that should be table-stakes for any credential worth the fee.

Transparent exam blueprint.

Every domain, weighting, and learning objective is published before a candidate sits the exam. No hidden rubric, no surprise question pools. If it is going to be tested, it is on the blueprint.

Open rubrics, graded on artifacts.

Higher tiers are not earned by memorized answers. They are earned by merged pull requests, governance memos, and live production deliveries — reviewed against rubrics a candidate can read in advance.

Independent audit from day one.

Exam integrity, rubric calibration, and grader performance are reviewed by people outside the company. We would rather a smaller pass rate with credibility than a generous one without it.

Tier gating by real work.

Associate, Practitioner, Master — each tier requires evidence of work done at that level. We do not certify intent. We certify delivery.

Where we are

Today

Building the standard.

Writing the SNCP blueprint, building the assessment platform, and talking to the first cohort of candidates, instructors, and enterprise design partners.

Next

First certification cohort.

A small, invite-only Associate and Practitioner cohort runs the five-stage assessment funnel end-to-end. Rubrics are stress-tested and the independent audit makes its first pass.

After that

Implementation marketplace opens.

Practitioner- and Master-tier holders become available to enterprise engagements through ScaledNative. Credentials plus shipped artifacts — not resumes — are what the buyer sees.

Ongoing

Public scorecard.

Pass rates, audit findings, remediation, and outcome data from implementation engagements will be published on a cadence. The standard is only credible if it can be inspected.

Who is building this.

ScaledNative is led by practitioners who have shipped production AI in regulated environments — not by consultants who write about it. The founding team is deliberately small and senior, drawn from engineering, applied research, and enterprise delivery.

Full leadership and instructor rosters will be published once named and onboarded. We would rather a quiet page today than inflated bios. If you are a senior practitioner who wants to help write the standard, the instructor track is open.

Implementation depth

When a ScaledNative engagement moves from operating-model design and practitioner enablement into deeper enterprise engineering, the implementation lane can pair with LockedIn Labs as the enterprise AI engineering and modernization delivery partner.

Explore the portfolio, then bring in the right layer.

If you are evaluating modernization software, collaboration systems, or the practitioner layer that helps those systems land, start the conversation here.