SnapLogic puts agents to work on legacy integration migration
SnapLogic has added an agentic engine to Intelligent Modernizer, its tool for moving old integration estates. Why migration is where AI can pay off first.
Almost every large organisation has an integration estate it would like to leave behind: an old ESB, a self-built message broker, or hundreds of flows in a platform that is reaching end of support. The problem is rarely the new platform. It is understanding what the old integrations actually do, often with poor documentation and the people who built them long gone.
On 22 September 2026, SnapLogic announced an agentic engine for Intelligent Modernizer (SLIM), its tool for analysing and migrating legacy integration workloads.
What is new
According to SnapLogic, the agentic engine adds:
- Broader platform support and intelligent discovery. SLIM can analyse different legacy technologies without a purpose-built connector for each source platform.
- Modernisation recommendations based on how the integrations relate to each other.
- Parallel agentic execution, so analysis runs faster.
- Enterprise governance with organisation-level administration, role-based access and visibility controls.
SLIM already covered workload analysis, migration planning, automated testing, documentation and generation of new pipelines. The press release does not name which legacy platforms are supported or give any figures, so that is the first thing to ask for.
SnapLogic’s CTO Jeremiah Stone makes a point worth noting: customers under pressure to consolidate “don’t want black-box modernization”. In other words, the tool has to show its reasoning, not just produce new pipelines.
Why migration is a good fit for AI
Migration is one of the areas where AI can pay off soonest in integration. The task is well defined: read old configuration, understand the logic, describe it and rebuild it in a new form. It is repetitive, but it requires understanding, which is exactly where language models are strong. And the result can be tested against the old solution, which makes quality measurable.
Gartner makes the same point in the 2026 Magic Quadrant for iPaaS, where SnapLogic is placed as a Visionary: modernising legacy integrations is a necessary step to prepare the architecture for AI.
How it compares
SnapLogic is not alone in using AI for migration. Most large vendors offer migration tools or partner programmes to move customers from competitors and from older on-premises platforms, and consultancies are building their own accelerators. What SnapLogic emphasises is that the analysis itself is done by agents, with governance and access control for the result.
What to ask
- Which sources? Which legacy platforms are actually supported, and how well?
- What comes out? Is the result documentation, a migration plan, finished pipelines, or all three?
- Testing. How is it verified that the new flow behaves like the old one, including error handling?
- Your code. Where is the old configuration analysed, and is it used to train models?
If you are planning a migration in the next year or two, it is worth running a limited proof of concept on a representative part of your estate. The documentation alone may be worth the effort.
Sources
This post was written with AI assistance and reviewed by the editor before publishing.