Case study

AI strategy, then an internal build that speeds up RFP responses

We worked with Knowit Cloud & Code's leadership to design an AI strategy and prioritize use cases, then led an internal development team to build the RFP matchmaker, which accelerates responses to IT project RFPs against a database of around a thousand consultant CVs and past projects.

Matching time
About a week, now a few hours
Managers no longer polled per RFP
Around 50
Data scope
Around 1,000 consultant CVs plus project history
Built by
Knowit's internal development team, led by us
Preceded by
AI playbook and prioritized use case portfolio

The situation

A consulting business answers RFPs for a living, and the quality of an answer depends on finding the right people and the most relevant past work fast. At Knowit Cloud & Code that meant searching across roughly a thousand consultant CVs and a history of delivered projects, under deadline, by people who could not possibly hold all of it in their heads. The wider question was where AI belonged across the business, for internal productivity and for what they offer clients.

What we did

Strategy first, then a deliberately chosen first build.

Why the RFP matchmaker was the right first build

It sat squarely on the first path to AI value, boosting productivity in a workflow the business already understood and already measured. The data existed. The owner was obvious. The result was visible to the people doing the work within one RFP cycle. Choosing a first build with those four properties is most of what determines whether an AI program gets a second one.

What changed

A small team of salespeople now matches consultants to an incoming RFP in a few hours. The same work used to take about a week. The larger change is what stopped happening: answering an RFP no longer means sending a question to fifty team managers to find out who is available and who fits. The search runs against the database rather than against fifty people’s attention, which is the part that had a real cost and never appeared on any budget line.

What the client said

Amir worked with us to establish an AI Playbook for both internal productivity and customer offerings. He engaged with both leadership and technical teams, as well as held several inspiration and enablement sessions for a wider audience. Through a good combination strategic approach, bias for action, and technical understanding, Amir proved invaluable in accelerating our AI journey and achieving tangible results.
Johan RibberklintCEO, Knowit Cloud & Code

Related: AI Use-Case Discovery and Prioritization · AI Implementation and Adoption

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