Grammarly for Proposals: How AI Experts Review Every Page Before You Send

Grammarly does not write your email. It makes sure what you send is right. Lurio is the same for proposals.

That one-sentence analogy does a lot of work. Let us unpack it.

What Grammarly Does

You write the email. Grammarly reads it and tells you: this sentence is passive, this word is overused, this tone reads as aggressive. It catches what you cannot see because you wrote it — you know what you meant, but a fresh pair of eyes reads what was actually written.

The email is still yours. Grammarly did not write a word of it. You decide what to change. You decide what to send.

The Equivalent Problem in Proposals

Business proposals — decks, pitch presentations, board packs, RFP responses — have the same problem, at higher stakes and higher complexity.

You run a discovery call. You produce the proposal. You read it three times. Then it goes to the client.

What you cannot see: whether the narrative logic actually holds. Whether the data figure on slide 6 contradicts the attribution model on slide 11. Whether the proof points are calibrated for a fintech CMO or a retail CFO — because you wrote it for both, which means it serves neither.

Senior partners catch these things. But senior partners cost £500 an hour and cannot review every proposal for every account manager at every agency in the country.

Five AI Experts, Every Page

Lurio's five curated experts are the Grammarly panel — but for proposals, not prose.

Strategy Critic reviews the narrative logic. Does the thesis hold? Is the argument structured from problem to evidence to conclusion? Are the claims supported by the data on the slide?

Brand Compliance checks every slide for visual and voice consistency against your brand guide. Colour usage, font weights, logo placement, tone of voice. One off-brand slide undermines the whole proposal.

Narrative Reviewer reads the story arc. Does slide 3 earn its place? Is the problem statement established before the solution is presented? Does the conclusion add anything, or does it repeat slides 2 through 4?

Data Integrity cross-checks numbers, sources, and internal consistency. It is looking for the CAC that contradicts the attribution model, the market size that lacks a methodology, the percentage that does not add up to 100.

Audience Fit evaluates ICP alignment. Are the proof points, benchmarks, and case studies calibrated for the specific buyer in the room — their industry, their seniority, their decision criteria? A fintech deck with retail benchmarks signals that the agency has not done their homework.

Cited, Not Guessed

The difference between useful critique and noise is grounding. Generic AI feedback — "this claim seems unsupported" — is noise. Specific, cited critique is signal.

Every observation from Lurio's experts is linked back to your knowledge base: your brand guide, your past-winning proposals, your client's website, your call transcripts. Not "this tone feels off" — "this paragraph deviates from the voice in your last three winning proposals for this sector."

That is what makes the analogy tight. Grammarly is not guessing about what good English looks like — it was trained on what good English looks like. Lurio's experts are not guessing about what a good proposal looks like for your firm and your clients. They were trained on your knowledge.

Your Sign-Off

Grammarly gives you the catch. You decide what to change. Same here.

Review the expert critiques. Accept the observations you agree with. Push back on the ones you do not. Edit the proposal accordingly. Sign off. Nothing leaves your firm without your approval.

The audit trail is yours: which experts ran, what they flagged, what changed between draft and send. Every communication that leaves your firm has provenance.

That is the Grammarly model — applied to the highest-stakes documents your business produces.