Anonymised case study · Enterprise

AI presales assistant for faster proposal preparation

A governed assistant helps teams find relevant experience, validate fit and assemble stronger proposal drafts.

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A commercial team using an AI assistant to prepare a business proposal

This case study is anonymised. Client identity, sensitive implementation detail and unsupported quantitative claims have been intentionally omitted.

Client context

A professional-services team preparing complex proposals from distributed experience and capability data.

Scope

Support evidence retrieval, candidate matching and controlled first-draft generation.

Core result

Less repetitive preparation with clearer traceability to approved source material.

Challenge

Teams searched across documents, CVs and previous work every time a proposal began. Reusing the right evidence depended on personal knowledge and left senior reviewers correcting avoidable inconsistencies.

Approach

The assistant retrieves from approved sources and separates evidence from generated narrative. Users can inspect citations, refine the brief and export a structured draft for human review.

Permission-aware knowledge retrieval
Structured opportunity and role requirements
Evidence-backed draft sections
Review, feedback and evaluation workflow

Outcome

Commercial teams begin with relevant evidence and a coherent structure. Experts remain accountable for the final proposal while repetitive search and assembly are reduced.

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What happens next

From first conversation to a clear path forward.

We begin with the operational reality, identify the decision that matters and keep the next step practical.

01
Your idea is treated confidentially, with an NDA available when needed.
02
You share the operational reality. We listen, map the constraints and ask direct questions.
03
You receive a clear view of the opportunity, risk and practical next steps.
04
Together, we align delivery around the outcomes that matter most.
05
You see early momentum as the plan moves into working systems and workflows.

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Tell us what is getting in the way.

Share the challenge, the systems involved and what a better outcome would change. We will come back with focused questions and a practical next step.

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