Someone on your team re-keys data from PDFs every day.
A pipeline that reads your documents, extracts the fields you need into structured data, checks them with rules, does the math in code, and sends only the uncertain fields to a person.
You have this problem if…
- Staff re-key invoices, leases, W-2s and 1099s, rate confirmations, bills of lading, rent rolls or T-12s into another system.
- You tried an AI tool. It read most fields but got some confidently wrong, and you can't tell which.
- The documents vary: scans, phone photos, and a different layout from every vendor.
What you get
- A pipeline running on 20–50 of your documents, producing structured output: a spreadsheet, JSON, or rows in your system
- Validation rules for each field: formats, ranges, and cross-checks between fields
- All arithmetic (totals, prorations, reconciliations) done in code, not by the model
- A review queue that sends only low-confidence fields to a person
- A field-level accuracy report: how often each field was right, and the confidence threshold chosen
How it is done
- 01
Define the fields
Which fields you need, in what format, and what counts as correct for each.
- 02
Label a sample
We record the correct values for 20–50 of your documents with you. This is the yardstick.
- 03
Extract
A model reads each document, constrained to your schema.
- 04
Validate
Rules and cross-checks catch impossible values, and the totals are recomputed in code.
- 05
Measure and set thresholds
Accuracy is measured per field, and confidence thresholds are set so the review queue stays a size your staff can handle.
- 06
Connect the output
Results go where you need them: a spreadsheet, a QuickBooks or Xero import, your CRM or your database.
What usually goes wrong, and how we handle it
Overall accuracy hides the fields that matter
"95% accurate" can mean every amount is right and every date is wrong. Accuracy is reported field by field.
Models make arithmetic mistakes
Sums, prorations and reconciliations are computed in code from the extracted values, never by the model.
A confident wrong value costs more than a blank one
Low-confidence fields go to a person instead of into your books.
Why you can trust us with this
A deterministic quality gate our founder built checks about 50,000 AI-generated items and catches about 1 in 10 on first pass. Extraction runs on the same idea: check the model's output with rules before anyone relies on it.
He also built analysis of 10-K and 10-Q filings with answers traceable to the source passage.
A quality gate for AI-generated content: 50,000 items checked, about 1 in 10 caught
Deterministic checks on every AI-generated item before it reaches a student. Failing items are pulled or regenerated automatically.
Case studyAnswers from SEC filings, each one traceable to its source
Question answering and summaries over 10-K and 10-Q filings and earnings calls. Report review time fell 95%.
What we don't do on this package
- No medical records or other health information (PHI).
- For tax preparers: return information goes to a model vendor only with the consent IRC §7216 requires. We build the consent step into the workflow.
- No automatic posting to your books without a review step, unless you turn it off.
Questions
What accuracy should we expect?
It depends on the documents, which is why the 10-document proof comes first. You get field-level numbers on your own files, not a vendor's benchmark.
Where do the documents go?
They stay in your cloud storage. They are processed through model APIs with data retention turned off where the vendor offers it.
Who does the work?
Suresh Rajendran, our founder, does the engineering on every engagement himself. Nothing is handed to a junior engineer or a subcontractor.
Where does our data go?
We work inside your accounts: your cloud, your repository, your model-vendor keys. Where a vendor offers zero data retention we turn it on, and your data is never used to train a model. Our access is removed and credentials are rotated at handover.
How do we pay?
The first step is paid up front. Builds are 50% to start and 50% on acceptance. We invoice from Destello AI Incorporated in US dollars, payable by ACH or card. If you go ahead with a build within 30 days of the first step, its fee is credited.
What if the result doesn't meet the bar?
Acceptance criteria are agreed in writing before work starts, and the second payment is due only when they're met.
Will you sign our NDA?
Yes, usually within one business day.
Start with the proof on 10 documents.
$750, credited to the build if you go ahead within 30 days. Book a 20-minute call, and you'll have a written scope with acceptance criteria within one business day.
Or email hello@destello.us or call (628) 202-5322. We reply within one business day.