Software rationalisation shouldn't be a four-month project.

Every software question at an enterprise arrives with another question attached. Who owns this tool? What does the team actually use it for? What breaks if it goes? Each answer requires a different person, a different system, a follow-up that may take two weeks to receive. The rationalisation analysis is rarely the bottleneck. The phone chain is.

The cost nobody tracks

The people running these projects are capable. That is what makes it so frustrating. Four months of calendar time is rarely four months of analysis. It is three or four weeks of actual work, stretched across sixteen weeks of waiting. App owners who do not respond. Second and third follow-ups. Information that turns out to be six months out of date. Starting over.

While the project runs, the estate keeps growing. Requests land every week. Renewals go through on autopilot because nobody had time to look. Someone comes back from a conference convinced a new tool is essential. Nobody has the bandwidth to check what the company already owns. Another duplicate gets approved.

The cost that never shows up on a dashboard is not just the duplicated spend. It is the drag. The always-behind. The capable team doing admin that a system should handle.

Rationalisation should be continuous

A single software question should not trigger a three-week investigation. The answer should already exist, because the work is reusable. The estate is known. The capabilities have already been compared. The contracts are already mapped.

That is what Sam does. You email sam@samplify.ai when a request comes in. Sam already knows your stack. It has already done the comparison. It returns one of four answers, BUY, RENEW, REPLACE or REJECT, with sources attached. In minutes, not months.

Four months of calendar time is rarely four months of analysis. It is three or four weeks of work, stretched across sixteen weeks of waiting.

That is the actual difference between a good demo and something an enterprise can genuinely run at scale.

What generic AI cannot do

SAM tools track what you own. They do not tell you what can replace what. SaaS platforms track usage and spend. They do not compare capabilities. EA systems map the architecture. They do not govern individual purchase requests. Generic AI can answer any question. It just does not know your stack, your policy, your contract context, or whether you already own the capability.

Sam sits above all of that. Stack-aware, so it already knows what you have. Feature-level, so it compares actual capability, not just category. Evidence-backed, so every answer has a source the approver can verify. Here is what that looks like on a real request:

The four teams that benefit most

Enterprise Architecture, SAM, Procurement, FinOps. Anyone who regularly receives questions such as 'should we buy this', 'can we remove this', or 'what do we already have that does this?' is a direct beneficiary.

The ROI framing is straightforward. Annual licence is around $100k. One avoided duplicate purchase covers the year. One bad renewal stopped is $250k or more. One category consolidation is $1M or more. Clients consistently save a minimum of 5% of annual software spend.

Starting before your data is clean

The most common reason enterprises delay is data quality. The estate is not fully catalogued. Contracts are scattered across teams. Usage data is incomplete. None of that is disqualifying. Sam works with imperfect data and learns as you go.

The PoV is thirty days, free, with no integration and nothing to install. Run it on real requests against your real estate. If the results do not justify continuing, walk away. That offer has never needed to be made twice. Start the thirty-day PoV and see what a five-minute answer looks like on requests that are currently taking months.