MLOps & LLMOps

Model Versioning & Registry Management

"Which model is actually running in production, and what data and code produced it" is a surprisingly hard question to answer once a team has more than one model and more than one environment. This service builds a structured model registry that ties every version to its training data, code commit, hyperparameters, and eval results, so lineage is traceable and rollback is a known path instead of a guess. It's for teams juggling multiple models or model versions across staging and production with no single source of truth for what's deployed where. The deliverable is a registry that makes reproducing, auditing, or rolling back any model version a lookup, not an investigation.

This is a capability we deliver for you as a service, not a role we’re hiring for.

How We’d Approach This

A clear, staged plan, not a black box

These are the service-specific steps inside our six-step process.

1
Diagnose how models are currently tracked, versioned, and promoted across training, staging, and production.
2
Pilot a structured registry on one model family, linking each version to its training data, code, and eval results.
3
Review the registry schema and promotion/rollback workflow with ML engineering before extending it further.
4
Roll out the registry across all production models, with rollback paths tested and documented for each.

What You Get

Deliverables from this engagement

Centralized model registry with full version lineage
Linked training data, code, and eval results per model version
Tested rollback procedure for every production model
Documented model promotion workflow from training to production

Six Ways We Could Architect This

Different engagement, different build, pick the shape that fits

There’s more than one way to deliver on this service. Browse a few of the ways we’d structure the work, depending on your speed, budget, and integration needs.

Read all 6 architectures as text

Lean Fast-Start Architecture

Manual Tracking

Model Artifact Produced
File Naming Convention Applied
Entry Added to Tracking Spreadsheet

Lineage Capture

Training Data Snapshot Noted
Code Commit Hash Recorded
Eval Results Attached

Promotion

Manual Promotion Decision
Git Tag Created for Version

Rollback Path

Prior Version Kept Accessible
Manual Rollback Instructions Documented
Rollback Tested Once

Cloud-Native / Managed Services Architecture

Managed Registry Layer

Managed Model Registry
Managed Artifact Storage
Training Pipeline Output

Lineage Operations

Linked Training Data Reference
Linked Code Commit and Hyperparameters
Linked Eval Results per Version

Promotion Operations

Staging Registry Stage
Production Registry Stage

Delivery Layer

Version Lookup Dashboard
Tested Rollback Path per Version
Promotion Workflow Documentation
Usage Reporting Across Models

Event-Driven & Automation-First Architecture

Triggers

Training Job Completes
Auto Register Model Version

Automation Layer

Auto Captured Lineage Metadata
Auto Triggered Eval Suite
Eval Meets Promotion Bar

Review Gate

Auto Flagged as Non Promotable
Auto Tagged as Promotion Candidate
Notification to ML Lead

Delivery

Promotion Approved
Auto Promoted to Production Stage
Prior Version Auto Archived for Rollback

Enterprise-Grade & Compliance-Ready Architecture

Governance Layer

Model Governance Policy
Promotion Approval Requirements
Access Control for Registry

Secure Registry

Role Based Registry Access
Immutable Version History
Redundant Artifact Backup

Auditable Lineage

Full Data Code and Eval Lineage
Independent Sign Off Before Production
Audit Log of Every Promotion

Compliance Delivery

Tested Rollback Procedure per Version
Audit Trail Export
Retention Schedule for Retired Versions

AI-Augmented, Human-in-the-Loop Architecture

Version Candidates

New Trained Model Version
Lineage Aggregation Engine
Historical Eval and Production Data

AI Analysis Layer

Auto Compiled Lineage Report
Promotion Recommendation Generated

Human in the Loop

ML Lead Reviews Lineage and Eval Report
Meets Promotion Bar
Send Back with Feedback
Human Approved Promotion

Delivery

Promoted to Production Registry Stage
Rollback Path Verified and Logged

Integration-Heavy / Ecosystem-Connected Architecture

Client Systems

Client Training Pipeline
Registry Integration Layer
Client Feature Store
Client CICD Pipeline

Registry Core

Centralized Model Registry
Version Lineage and Promotion Engine

Two Way Sync Layer

Client Data Warehouse Sync
Client BI Tool Sync
Model Performance Reporting
Executive Dashboard

Shared Governance

Joint Review with Client ML Team
Published Registry and Rollback Guide

Ready to get started?

Tell us what you’re trying to get done and we’ll help you find the highest-leverage place to start, scoped small enough to prove itself before you commit to anything bigger.

Talk to us about Model Versioning & Registry Management

Most engagements like this start as a $500–$2,500 pilot, see full pricing.