Opportunities › Affordable OCR processing at scale › Proposed app
Batchleaf
Low-cost bulk OCR with bounding boxes, by API or drag-and-drop batch
- Score
- 50
- confidence 66
- Evidence
- 18
- items on the page
- Rivals
- 6
- named in sources
- First version
- 30 d
- estimate
- Type
- Desktop app
- PWA: runs in the browser, installs on Mac and Windows
- Market since
- 2016
- Established market · AI estimate
ScreensConcept
Desktop app: Batch processing, queue management, and visual verification of OCR output require a full dashboard—work done at a desk. Sample screens on a computer, in the proposed brand. Their numbers are sample data.
New batch
Ready to run$0.58
About this appAI proposal
Batchleaf turns large piles of scanned pages and PDFs into text and bounding boxes. Send files through an API or drop a folder into the web app, and get back JSON, plain text or searchable PDFs, with word and line coordinates for grounding.
It is built for developers and operations teams who run document pipelines with thousands of pages a week and find per-page pricing hard to justify. The material shows users calling $3.50 per 1,000 pages too expensive and some vendors absurdly expensive. Batchleaf aims to undercut them.
Every job shows its cost before it runs and its real cost after. Pages that look uncertain are flagged for review instead of silently passed on, so a cheap run does not turn into bad data downstream.
- Tagline
- Read every page. Pay for far fewer of them.
- Voice
- PlainFrugalPrecise
- Why this name
- A leaf is a sheet of paper, and a batch is the pile. The name is two plain syllables and says what the product does: read paper in bulk.
In the first version
Members say which features they would use. It tells PWAS what people want; it changes no score.
Bounding boxes on every page
Word, line and block coordinates in JSON, so you can highlight sources, ground LLM answers and crop regions.
No member yet
Cost shown before you run
Upload a batch and see the estimated price per 1,000 pages and the total first. The final bill is shown per job.
No member yet
Batch queue with webhooks
Submit thousands of pages at once, track progress, and get a webhook when each job finishes or fails.
No member yet
Confidence flags
Low-confidence pages and regions are marked, so you can re-run or review only those instead of the whole batch.
No member yet
Brand identityAI proposal
Check the name against trademark registers before using it.
Palette
#14342BDeep Fern · primary#F6F3EAPaper · surface#1B2A25Ink · text#E8742ASignal Orange · accent, bounding boxes#2F7D6BSage · data and success
Typography
Aa
Batchleaf
ABCDEFGHIJKLMNOPQRSTUVWXYZ 0123456789
Read every page. Pay for far fewer of them.
PricingAI proposal
The material gives claimed per-1,000-page prices ($1.50 Google, $3.50-$4 Mistral, $10 Reducto Parse) and a verified $500 a month Extend plan. Tiers sit below these as a starting point to test.
Free
Free
- 500 pages a month
- Full bounding boxes
- Web app and API
Starter
$29 a month
- 50,000 pages included
- Webhooks and spend caps
- Extra pages billed per 1,000
Scale
$149 a month
- 500,000 pages included
- Batch priority queue
- Usage alerts and 3 API keys
- Email support
Volume
Contact us
What it could be worthEstimate
What a software business making this much sells for today, from real deals. Pick a monthly revenue.
If it makes
Worth about
$194,000
Sale range $132,000 to $263,000
$120,000 a year in revenue
From 87 software businesses listed and sold on Empire Flippers in the last year, revenue vetted by the broker: they sell for about 19× their monthly revenue, most between 13× and 26×.
Measured on profit, the middle deal is 32× monthly net profit: about 2.7 years of profit.
An estimate, not an offer or financial advice. A real price depends on profit, growth, churn, how much of the work is the owner's, and the buyer.
How it would growAI proposal
How the product would reach new customers through its own use, and how the first ones would be found. A plan to test, not a result.
- Built-in loop
- No loop in the product. Customers call an API behind their own pipelines, so end users never see Batchleaf. Growth comes from developer content, open benchmarks, docs and a free tier that people try on their own batches.
- Do they become customers?
- The people reached are the buyers: developers who feel the per-page cost. Test whether a free-tier user with a real batch moves to a paid plan within 30 days.
- First customers
- Small teams of 2-10 developers building AI document pipelines (RAG, invoice or archive digitising) that process over 50,000 pages a month and now pay a commercial OCR API.
- Where to reach them
- Hacker News and developer forums: Post a public benchmark with cost, speed and box accuracy on real documents, and answer questions in threads about OCR cost.
- Direct outreach to pipeline builders: Offer a free run of one customer batch, with a side-by-side cost and quality report against their current API.
- Open-source integrations: Publish small connectors for popular LLM and document-processing libraries so people can switch with a few lines.
- First milestone
- Five teams each paying for at least 50,000 pages a month within 60 days, after a side-by-side test on their own documents.
Why people already pay for this
- Public claimThe commenter operates an OCR pipeline processing around 1000 pages for $0.05-0.10 USD with approximately 0.8 seconds per page turnaround and full bounding box support.
- Public claimExisting OCR services charge $3.50 per 1000 pages, which users perceive as too expensive for their use case.
- VerifiedHacker News post received 17 points and 11 comments
- Public claimLeading open-weight OCR models now match or exceed proprietary offerings in quality
- Public claim
Tech stack
Every proposal builds on the same PWA base, installable from the browser on any phone or computer. Dashed boxes are what this app adds.
- AppNext.js and TypeScript
- PWAManifest and service worker
- UITailwind CSS
- Data and authSupabase Postgres
- PaymentsStripe
- EmailResend
- HostingVercel
- This app · OCR inferenceOpen-weight OCR models on rented GPUsThe cost advantage depends on running strong open models on rented GPU capacity, not reselling another API.
- This app · Job queue and workersQueue service with autoscaling GPU workersBatches of thousands of pages need retries, progress tracking and scaling to zero when idle.
RisksAI inference
- CommercialThe cost claim comes from one unverified comment. Real cost per page, including idle GPUs, retries and hard documents, may leave little margin at these prices.
- TechnicalOpen models vary on tables, handwriting, low-quality scans and non-Latin scripts. Bounding box accuracy must be measured against what buyers use today.
- CommercialMistral and Google can cut prices, and buyers may stay with a larger vendor they already trust for compliance reasons.
- RegulatoryDocuments may hold personal or financial data. Buyers will ask about retention, data location and certifications that a small team lacks at launch.
- PlatformGPU rental prices and availability change. Model licences must allow paid commercial hosting, and each one needs checking.
Everything marked AI proposal or AI inference was written by a model from the evidence on the opportunity page. The proposed name must be checked against trademark registers before it is used.