A reason to choose
The agency can choose between three diagnostics-lab ad drafts using a relative score and its breakdown, rather than picking by feel before committing a client's ad budget to one of them.
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In build
The whole team
Nineteen specialists, each with a defined job and an honest status label.
See all nineteenThe business picks the stronger of several drafts before spending money on ads, instead of guessing.
Works with
What it does
Each generated variation gets a relative score estimating how well it's likely to perform for the stated goal (clicks, opens, engagement), based on patterns in past high- and low-performing copy. The score is directional, not a guarantee, and the user can request a "boost" rewrite aimed at improving it.
A marketing agency has three ad-copy drafts for a client's diagnostics-lab campaign and a limited budget to actually run against real audiences — picking the wrong one wastes money the agency has to justify to the client afterwards. Choosing by gut feel between three plausible-sounding drafts isn't a great use of a client's ad spend.
Each generated variation gets a relative score estimating how well it's likely to perform for the stated goal — clicks, opens, engagement — based on patterns found in past high- and low-performing copy for that category. The score is explicitly directional, not a promise, and a "boost" option offers a targeted rewrite aimed at improving whichever factor scored lowest.
Lekha runs this directly on the platforms your customers already use — no separate app for them to install.
How it works
Each generated draft is compared to patterns in a chosen industry dataset's historical high- and low-performing copy, producing a relative score rather than an absolute promise of results, since no access exists to the actual conversion data behind those past campaigns.
Beyond a single number, the scoring shows which specific elements — the opening line, the call-to-action, the length — are pulling the score up or down, giving a reason behind the number rather than just the number alone.
Requesting a boost triggers a rewrite specifically aimed at improving the lowest-scoring factor identified, rather than a generic full rewrite that might improve one thing while quietly weakening another element that was already scoring well before the request was made.
Every score is shown alongside which industry dataset it was compared against, since a score means something different depending on which category of past copy it was actually measured relative to, and that context matters when comparing two drafts scored on different runs.
Why it matters
The agency can choose between three diagnostics-lab ad drafts using a relative score and its breakdown, rather than picking by feel before committing a client's ad budget to one of them.
A low score comes with the specific factor driving it, so a rewrite can target exactly what's underperforming instead of guessing at what to fix across the whole draft.
The boost option rewrites toward the identified weak factor specifically, saving the effort of redrafting an otherwise strong piece of copy from scratch over one weak element.
The detail
The single most important thing to understand about this score is what it is not: a guarantee, or a measurement of the business's own actual audience. It's a directional estimate built from patterns in a chosen industry dataset — what has correlated with performance in similar past copy — not a live read on how this ad will do with this diagnostics lab's own customers, because there is no access to that business's real conversion data behind the score. Two ads with identical scores can perform very differently once run, and that gap is the score's honest limitation.
A score with no real outcome data behind it can create a subtle danger: false confidence. A team that treats a 78 as reliably better than a 71 is trusting a precision the method doesn't support — the score is a relative signal worth using as one input among several, not a number precise enough to bet a campaign's entire strategy on alone, unchecked against anything else the team knows about its own audience.
Where a business connects its own ad-platform account, the score can be benchmarked against its actual historical campaigns rather than only a generic dataset, which meaningfully improves relevance — a score compared to the agency's own past diagnostics-lab campaigns says more than one compared to a broad, generic sample. Without that connection, the score remains a generic-category estimate, worth knowing before deciding how much weight to put on it in a real budget decision.
Industry use cases
12 industries where Lekha applies this directly.
A sales manager sets up a persona for "IT decision-maker at a mid-size manufacturer," and every rep on the team generates cold-email drafts from the same persona so outreach feels coordinated rather than ad hoc.
See the b2b sales playbookA regional NBFC drafts a loan-product social post, and Lekha flags the line mentioning an interest rate range as a regulated claim, holding the post in a pending-review queue until the compliance officer confirms the number matches the current approved rate sheet.
See the banking and finance playbookA skincare brand uploads its full product line as a spreadsheet with ingredients and benefits per item, and Lekha generates a description and a caption for each product in one bulk run instead of one at a time.
See the beauty and cosmetics playbookA test-prep institute asks Lekha for a blog post targeting the keyword "best online coaching for class 10 boards," and Lekha returns a structured draft with headings and an FAQ section, with any specific outcome claim about pass rates flagged for the institute to verify before publishing.
See the education playbookA freelance interior consultant uses Lekha to turn one client project photo caption into a LinkedIn post, an Instagram caption, and a one-line portfolio blurb, all in the same evening.
See the freelancers and consultants playbookA physiotherapy clinic drafts a social post about a new treatment offering, and Lekha flags the phrase implying guaranteed pain relief as a health claim needing review, holding it until the treating physiotherapist approves the wording.
See the health and wellness playbookA furniture retailer uploads a new collection's specs and Lekha drafts descriptions for the e-commerce listing plus a matching Instagram caption set, keeping material and dimension details exactly as supplied.
See the home decor and furnishing playbookAn agency managing five retail clients keeps five separate brand-voice profiles in Lekha, so the same campaign-brief-to-assets workflow produces distinctly different-sounding output for each client from the same underlying template.
See the marketing agencies playbookA broker pastes a property's square footage, bedroom count, and location, and Lekha drafts a listing description and a short email to interested buyers, both built strictly from the supplied facts.
See the real estate playbookA restaurant launching a new seasonal menu pastes the dish names and ingredients, and Lekha generates a description for each dish plus a launch-announcement caption, ready to review before the menu print deadline.
See the restaurants and food playbookA day spa asks Lekha to write copy for a new facial package, and Lekha drafts the description but flags a line implying a specific skin-improvement result as needing the owner's confirmation before it's used in an ad.
See the spas and salons playbookA tour operator asks for a Kerala backwaters package description in both English and Hindi, and Lekha produces two natural-reading versions rather than a literal translation of one into the other.
See the travel and tourism playbookMore from Lekha
The business gets copy that consistently sounds like them, in every language, without re-explaining tone in every prompt.
Learn moreThe business drafts a usable first version of an ad, caption, email, or product description in seconds instead of starting from a blank page.
Learn moreThe business can dial a single draft from formal to playful (or vice versa) without rewriting it from scratch.
Learn moreThe business reaches Hindi-speaking and code-mixed audiences with copy that reads naturally, not like a literal translation.
Learn moreThe business turns one piece of English copy into ready-to-use versions in other languages without hiring a translator for routine content.
Learn moreThe business gets a blog post or landing page draft built around a target keyword, ready to publish with minimal editing.
Learn moreQuestions
Not guaranteed — the score is a directional estimate built from patterns in a chosen industry dataset, not a measurement of how this specific ad will do with this specific business's actual audience, since there's no access to the business's real conversion data behind the score. Two drafts with the same score can still perform differently once actually run, and that's an honest limitation of the method, not a fault in how the number was calculated.
Treat it as a relative signal rather than a precise measurement — the scoring method isn't built to support that level of confident distinction between two close numbers, and reading too much into a small gap is a common way this tool gets over-trusted. It's more useful for spotting a clearly weaker draft among several options than for deciding between two that scored close together.
Yes, if the business connects its own ad-platform account, scores can be benchmarked against that business's own historical campaign performance rather than only a generic industry-wide dataset, which is meaningfully more relevant to the actual audience being reached. Without that connection, the score defaults to comparing against the broader chosen category, which is still a real but more generic directional signal.
It targets specifically the factor that scored lowest in the breakdown — the opening line, the call-to-action, whatever was identified as the weak spot — rather than rewriting the whole draft from scratch. This means a boost can improve one dimension while the rest of the copy stays largely as it was, which is usually preferable to a full rewrite risking a strong element for no reason.
The rest of your stack
No rip-and-replace — predict which draft performs best works alongside the systems already running your business.
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