Turn paper into searchable files and structured data. We convert your documents, index them to your rules and pass the fields into your system, with AI doing the typing and checks catching the exceptions.
A scanned page is only a picture until something reads it. We work in three layers, and you can stop at whichever one you need.
Every page scanned and run through OCR, so text can be searched and copied. Included in standard scanning.
Files named and organised by their contents, using the references, dates and conventions your business already uses.
Names, dates, amounts and reference numbers extracted from each document and passed to the right record.
Manual data entry is slow and invites mistakes. We use AI to read each document and extract the fields you need, then apply validation rules: mandatory fields present, dates in a valid format, references that match a record. Anything the rules or the AI are unsure about goes to a person.
You approve the rules on a real sample first, so you know what accuracy to expect on your documents before the full job runs. We do not quote an accuracy figure without one.
Standard scanning includes OCR and delivery. Optional AI naming and metadata tagging is from $1.20 per 1,000 pages. CRM integration or a searchable cloud document library is included on contracts of 6 months or longer. Bespoke extraction flows are quoted after we see your documents. See the full price list.
For connecting extracted data to the rest of your business, see custom workflows. For how documents are named and tagged, see AI indexing.
Document conversion turns paper into searchable digital files that are named and organised sensibly. Data entry takes the information inside those documents, such as names, dates and amounts, and puts it into fields in a system. Most projects need both.
Extraction is done by AI, with rules that check each result and send anything uncertain to a person for review. You see how this performs on your own documents before you commit.
Handwriting, faded paper and damaged originals are harder to read accurately. We test your sample before quoting so you can see exactly what is and is not readable.
SharePoint, a CRM or job system that supports an API or suitable import, or a document portal we build. We confirm the available access and matching rules during scoping.
Tell us roughly how many boxes and what is in them, and we will come back with a quote. Collection is quoted separately.