Case Study / Agentic AI · Finance · Document Processing
Deployed forSyslatechHow Syslatech automates finance documents with human oversight
A production pipeline on Amazon Bedrock processes about 77% of finance documents without human intervention, sends uncertain cases to reviewers, and records every decision.
- Client
- Syslatech
- Industry
- Finance · Document Processing
- Platform
- Amazon Bedrock
- Status
- Live in production since July 2026
Measured impact
Documents processed straight through, no human touch
Modelled reduction in monthly processing cost
Audit coverage across every document processed
Human reviewer in the loop for low-confidence documents
01 / Overview
The operating context.
Syslatech's finance team was processing incoming documents by hand — reading, keying, and cross-checking every invoice, receipt, and form before it could move into their systems. It was slow, it didn't scale, and small errors were easy to miss under volume.
Algorims designed and delivered a generative AI-powered document processing pipeline built entirely on AWS, giving Syslatech a faster, more consistent way to process documents — without losing the accuracy or oversight a finance team depends on.
02 / Challenge
What stood in the way.
Syslatech's finance team needed a faster way to process high volumes of documents without losing the accuracy or oversight the job demands:
- 01
Every invoice, receipt, and form was read, keyed, and cross-checked by hand before it could move into Syslatech's systems.
- 02
Manual review didn't scale — volume grew faster than the team's capacity to keep up.
- 03
Small errors were easy to miss under volume, with no consistent way to catch them.
- 04
Ad hoc use of consumer AI tools sped some work up, but created its own data-handling concerns.
03 / Solution
What Algorims built
A generative AI-powered document processing pipeline built entirely on AWS, using a tiered extraction model on Amazon Bedrock so a fast, cost-efficient model handles most documents automatically — and only the ones it's unsure about get escalated.
Tiered extraction on Bedrock
Most documents are read and structured automatically by a fast, cost-efficient model. Anything the system is less confident about is automatically escalated to a more powerful model.
Human in the loop
If confidence still isn't high enough after escalation, the document is routed to a human reviewer before it ever reaches Syslatech's records — the AI never guesses on the finance team's behalf.
Full audit trail
Every decision, every escalation, and every human correction is logged, giving Syslatech a complete, reviewable record of exactly how each document was handled.
System stack
Production foundations.
- Amazon Bedrock
- AWS Step Functions
- AWS Lambda
- Amazon S3
- Infrastructure as Code
04 / Results
What changed after delivery.
~77% straight-through processing — documents processed automatically with no human touch at all.
99.6% modelled cost reduction — in monthly document-processing cost compared to the prior manual/ad hoc process, at current production volume.
100% audit coverage — every document's processing history, confidence score, and any human correction is recorded and reviewable.
Live in production since July 2026, continuing to process Syslatech's day-to-day document volume.