SIs + Datafold: Better partners than competitors

The trillion-dollar SI and consulting industry is facing its biggest disruption in decades on the data engineering front. AI-powered solutions can now automate complex code translation and validation work that previously required armies of consultants and months of manual labor. For many SIs, the natural reaction is to view this as a threat.

We've been working with several SI partners over the past year, and we're seeing a different story emerge—one where a stealth AI technology partner becomes a force multiplier rather than a replacement.

The old playbook is breaking down

Traditional migration economics are brutal. SIs bid time-and-materials contracts for projects with inherently unpredictable scope. Legacy code bases are full of undocumented business logic, edge cases, and technical debt accumulated over decades. What starts as a 12-month project easily stretches to 18 or 24 months as teams discover new complexities.

Meanwhile, clients are getting smarter. They're asking harder questions about timelines and cost predictability. They're benchmarking proposals against emerging AI-first alternatives that promise faster delivery at a fraction of the cost.

The result? A race to the bottom on pricing, razor-thin margins, and burned-out engineering teams working impossible deadlines.

A different value proposition

At Datafold, we've automated the most labor-intensive part of migrations: code translation and validation. Our AI Migration Agent can handle any SQL dialect, ETL workflow, or stored procedure logic while our data diffing technology guarantees mathematical accuracy between source and target systems.

Tooling itself isn’t a novel concept. Most SIs aren't doing everything manually anymore. Many have built their own homegrown code conversion engines over the years, while others leverage tools like SnowConvert, BQMS, or Lakebridge (now part of Databricks). These tools work reasonably well for straightforward SQL translation, but they struggle with the complexity of modern enterprise environments—especially when you're dealing with stacked systems that combine multiple ETL platforms, legacy warehouses, and decades of accumulated business logic embedded in stored procedures and workflows.

What we're hearing from SI teams is that their existing toolsets, while helpful, aren't really up to the task when migrations get complex. They still end up doing significant manual work to handle edge cases, validate outputs, and deal with the architectural differences between source and target systems. That gap between what their current tools can handle and a purpose-built AI agent can accomplish is where we see the partnership opportunity.

What we're seeing in practice

We've been working closely with a handful of great SI teams and the results have been pretty compelling. When they partner with Datafold, they can:

• Win more deals by offering guaranteed timelines and fixed pricing that clients increasingly demand
• Improve margins dramatically by automating the highest-cost, lowest-margin work
• Redeploy senior talent to higher-value activities like architecture design and business process optimization
• Differentiate on speed and certainty rather than competing solely on hourly rates

We've seen this play out successfully with multiple partners, including a top 3 GSI who has now won multiple migration deals by leveraging our technology as their underlying execution engine.

Beyond the migration

Migration is just the beginning of the client relationship. Once legacy workloads are successfully migrated, clients need help maximizing their new platform capabilities. This is where SIs provide irreplaceable value: education, enablement, and the development of new analytics capabilities that drive business outcomes.

AI can automate code translation, but it can't facilitate organizational change management or help business users understand how to leverage new self-service analytics capabilities. Those are fundamentally human challenges that require the relationship-building and consultative expertise that SIs have developed over time.

The path forward

I’m bullish on AI's ability to automate more data engineering workflows over time. Translation and validation are just the beginning. But I’m equally convinced that the future belongs to partnerships that combine AI's execution capabilities with human expertise in relationship management and business transformation.

For SIs willing to evolve their approach, this represents an opportunity. Rather than competing on the commodity work of code translation, they can compete on business outcomes and client success. Rather than managing delivery risk on unpredictable timelines, they can offer clients the certainty they increasingly demand.

The question isn't whether AI will disrupt traditional migration services—it already has. The question is how firms adapt to that reality.

We're seeing some interesting partnerships emerge from teams that view AI not as a threat to their business model, but as a tool that lets them focus on what they do best.

If you’re ready to evolve your approach, let’s talk.