Extraction with the structure you need
Not raw text. The fields, tables and relationships your downstream system expects, in the shape it expects them.
Solutions
Document Intelligence
Turning documents into structured data that the rest of your systems can actually use.
What we would actually build
Classification and routing
Work out what a document is and where it should go, so that the sorting nobody enjoys stops being somebody's morning.
Review built for the exceptions
The hard documents will always need a human. The interface for those should be designed as carefully as the automation for the rest.
How this would go
The parts people get burned on.
Accuracy is stated, not implied
We measure against a set you label yourselves, and we report the number we get rather than the number we hoped for.
The messy sample, not the clean one
Scans, photographs, bad rotations and the one supplier who still faxes. Building against tidy examples is how these projects fail in month three.
Confidence surfaced to the operator
The person reviewing needs to know which fields to check. Hiding uncertainty makes the whole output untrustworthy.
Who we have done it for
One engagement, and a direct one: a screenplay goes in and the master breakdown a production team works from comes out.
Mythus AI Studios
Direct client
A desktop application for the film industry, on Mac and Windows. It reads a screenplay and produces the master breakdown directly, as one place for a production team to work.
Every engagement SpazorLabs has delivered is listed on the work page, with the relationship stated on each one.
Also in Solutions
Where to start
Tell us what you are trying to build
Send us the problem, not a specification. We will tell you what we think it actually takes, and we will tell you if we are not the right people for it.