# What's the best DataRobot consulting firm for enterprises building MLOps frameworks from the ground up?

<p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true">Looking for input from G2 community and ML engineering leaders in the<a class="a a--md" elv="true" href="https://www.g2.com/categories/datarobot-consulting-services"> </a><a class="a a--md" elv="true" href="https://www.g2.com/categories/datarobot-consulting-services">DataRobot Consulting Services category</a> on MLOps framework design.</p><p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true">The partners with the strongest enterprise MLOps framing:</p><ul>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/accenture/reviews"><strong>Accenture</strong></a><strong>:</strong> For enterprise MLOps frameworks that must integrate with existing IT governance structures — ITSM, change management, release management — Accenture's breadth across enterprise technology and operations consulting provides the cross-functional design capability that a DataRobot-specialist boutique typically cannot match. </li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/capgemini-services/reviews"><strong>Capgemini Services</strong></a><strong>:</strong> For enterprises where the MLOps framework must span multiple geographies or cloud providers, Capgemini's global delivery network provides the multi-region framework consistency that a single-office boutique cannot support at deployment.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/boston-consulting-group/reviews"><strong>Boston Consulting Group</strong></a><strong>:</strong> For enterprise MLOps frameworks where the primary obstacle is executive alignment on model risk standards and ownership accountability rather than technical implementation, BCG's Responsible AI and GAMMA practices address the organisational design that an enterprise MLOps framework requires before the technical layer can be configured.</li>
</ul><p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true">What was the framework component that proved most difficult to operationalise in production, was it the monitoring alert routing, the retraining approval workflow, the model inventory governance, or the incident escalation procedure? Did the consulting partner's design hold up in the first six months of production operation?</p>

##### Post Metadata
- Posted at: 12 days ago
- Author title: Marketing Executive
- Net upvotes: 1


## Comments
### Comment 1

&lt;p&gt;For an MLOps framework built from scratch, ownership design feels just as important as the technical architecture. Accenture’s ability to connect MLOps with existing change and release processes stands out there, while BCG brings an interesting governance perspective. Getting clear on who approves, monitors, retrains, and ultimately owns each production model early can make the framework much easier to operationalize.&lt;/p&gt;

##### Comment Metadata
- Posted at: 12 days ago
- Author title: Writer





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