- Enterprise integration + AI for the business

Connect your enterprise.
Make it AI-ready.

We connect the applications, data, and processes your business runs on, then make that backbone safe for AI to act on. For leaders who need integration to show up as faster cycle times, lower operating cost, and less risk, not another IT project that stalls.


The cost of disconnected systems

Disconnected systems quietly tax every quarter.

When systems do not connect, the cost hides in plain sight: slower cycle times, manual rework, stalled AI pilots, and decisions made on stale data. None of it shows up as a single line item, which is exactly why it keeps growing until someone has to deal with it.

Manual handoffs

People re-key and reconcile data between tools that should already talk, so work waits on someone being at their desk.

Stalled AI pilots

AI stalls on access, not the model. Agents cannot safely reach the systems where the work actually happens.

Stale decisions

Siloed data means leadership reporting lags reality, so the business reacts late and corrects course after the fact.

Compounding integration debt

Point-to-point fixes pile up, so every new change costs more than the last and the next platform decision gets harder.

Every quarter without a connected backbone adds rework, delays the return on AI, and grows integration debt that someone eventually has to pay down.

How we help

Four things we connect, in plain terms.

We cover the full path from connecting systems to running AI safely on top of them. Here it is for the business, with the technical detail one click away for your architects.

1

Connect your systems

Applications, databases, SaaS, and partners (SAP, Salesforce, Workday, ServiceNow, and more) exchange data reliably, on-premise and in the cloud.

2

Automate your processes

Approvals, exceptions, and workflows run end to end across systems instead of stopping at each handoff.

3

Make it AI-ready

Your systems are exposed to AI agents through controlled interfaces, so AI can act without direct access to core systems.

4

Keep it governed

Security, approvals, logging, and cost controls are part of the design, not an afterthought.

Go deeper

Explore integration in depth.

Two paths, depending on what you need next: the full integration practice, or the AI-ready architecture built on top of it.

Integration in depth

Integration Solutions

Platforms, partnerships, and delivery in depth: SnapLogic, MuleSoft, Boomi, Informatica, TIBCO, and Camunda, plus API management, messaging, and ETL.

Explore Integration Solutions
AI enterprise integration

AI Enterprise Integration

The reference architecture, LLM and API gateways, MCP, governance, and patterns that let AI agents read, reason, and act safely across your systems.

Explore AI Integration
Built by IWConnect

Your integrations shouldn't live in one person's head.

When that person leaves, the knowledge leaves too. Pete writes clear, always-current documentation for every SnapLogic pipeline, automatically.


  • Document a pipeline in seconds, not a sprint
  • Docs that stay in sync on their own
  • Onboard and hand over without the guesswork
Explore Pete
Proof

Proof you can read in full.

Published case studies from production work. Different industries, the same foundation: connect the systems, trust the data, and let analytics and AI run on top.

Featured image for the European bank SnapLogic loan approval case study
Banking

Under 30 min

Loan approvals

A European bank connected seven back-end systems through one SnapLogic layer, so loan decisions happen while the customer is still in the branch. Processing is 60 to 80% faster, with 99.5%+ availability.

Read the case study
Featured image for the Snowflake data governance manufacturing case study
Manufacturing

5x faster

M&A data integration

A global manufacturer unified a fragmented post-merger data estate into a governed, AI-ready Snowflake foundation, making acquisition data integration about five times faster.

Read the case study
Featured image for the global retailer AI error triage case study
Retail

90%

Errors auto-classified

A global retailer turned integration error storms into a self-learning classification pipeline using SnapLogic, Gemini, and Qdrant. More than 90% of recurring errors are now processed automatically.

Read the case study

More proof

Read the full library of IWConnect data, AI, application, cloud, and integration case studies.

Browse all case studies
What changes for the business

From manual workarounds to a connected backbone.

The point of connecting systems is not the connection. It is what changes for the business once the connection exists, while most organizations are still stuck on the wrong side of it.

95%of enterprise AI pilots fail to scale, on integration and data, not the modelMIT, 2025
11%of enterprises actually run AI agents in production todayIndustry research, 2026
40%of enterprise apps will embed task-specific AI agents by the end of 2026Gartner
Time to value Work crawls between systems over days Cycle times drop to minutes
Cost People re-key, reconcile, and chase status by hand Integrations run without supervision
Defensibility AI pilots stall before they reach production Agents run in production through governed interfaces
Risk Audit preparation is manual and slow Every action is logged and audit-ready
Where to start

Start with a focused assessment, not a year-long program.

You do not have to commit to a platform migration to find out if this pays off. Start with a short, scoped engagement that gives you a clear picture and a costed plan.

  • A map of your current systems and integration gaps
  • One or two high-value use cases identified and scoped
  • A costed, sequenced plan you can take to the board
  • A clear view of what AI can safely do across your systems
1 Discover 2 Map & scope 3 Costed plan
Why IWConnect

Why teams pick us over the other three vendors on the shortlist.

Most integration vendors look the same on a slide. Here is what is different in practice.

Vendor-neutral

We are not reselling one platform. We work across SnapLogic, MuleSoft, Boomi, Informatica, and others, and recommend the combination that fits your stack, not our margin.

Integration is our core practice

Integration is not a side practice for us. We have delivered it across industries and successive platform generations.

We build, not just advise

Pete, our SnapLogic documentation assistant, is a shipping product our own teams use. We deliver working software, not slide decks.

Governance-first for AI

We treat AI access to your systems as something to control and audit from day one. That is what makes it safe to put in production.

Who this is for. Best fit if you run several disconnected systems and want AI to do real work across them. If you have a single source of truth and no near-term AI plans, you probably do not need this yet.

Get started

See where a connected, AI-ready backbone would pay off first.

Bring your two or three most painful system gaps. We will tell you which ones are worth connecting first and what it would take.

Questions leaders ask

The questions that come up on the first call.

What does this cost, and when do we see value?

Most engagements start with a short, scoped assessment that produces a costed plan, so you see the shape of the investment and the first use case before committing to a build.

We tried integration before and it stalled. Why is this different?

Stalls usually come from trying to connect everything at once. We start with one or two high-value use cases, ship them, then reuse the pattern, so value lands early instead of at the end of a multi-year program.

What happens to this after your team leaves?

We build with reusable patterns and documentation, and hand over to your team with the records needed to maintain it. Knowledge transfer is part of delivery, not an upsell.

Do we have to replace our current integration platform?

No. We work with what you already run and add to it. We are vendor-neutral, so the recommendation is based on your stack, not a product we resell.

Is it safe to let AI act on our core systems?

AI reaches your systems through governed interfaces with authentication, approvals, logging, and cost controls. Every action is traceable, the same way regular API traffic is.