KYC extraction, bank statement parsing and fraud checks, tested on right-sized models against your evals, with where the data is processed agreed first.
Prefer email? hello@azitalabs.com, subject “Workload evaluation: Fintech product”
Your app pulls names from bank statements, checks KYC documents and flags fraud before onboarding. Simple extraction steps run on frontier models, and your own policies and your partners' contracts decide where regulated data may be processed. Every user feels onboarding latency, and you cannot tune the endpoints you rent.
An example workflow
Bank statements are parsed for income and obligations before every loan decision. An evaluation could run a labelled sample where the lender's rules allow and compare parsing accuracy and total cost with the current provider.
An example workflow
Merchant onboarding needs documents checked quickly and consistently. An evaluation could profile the verification pipeline step by step and compare pass rates, latency and total cost.
An example workflow
Fraud signals are summarised for analysts on every flagged transaction. An evaluation could replay a sample of flagged cases and compare the summaries analysts would accept, and what they would cost.
Every step is judged against your risk team's evals. A step that does not pass stays where it is.
Extraction and classification steps are matched to models sized to them, and checks that need a larger model keep it.
Each verification step's total cost compared with what you pay today, before you switch.
Run your workload on capacity from Azita’s installations. Scope the workload and data requirements.
Discuss your workload on the fleetScope the room and workload together. Azita designs, installs and commissions the deployment.
Discuss an installation in your buildingWhere the work runs, which models are used, who has access and how long anything is kept are agreed in your proposal before any work starts. The Trust page sets out custody and residency by side.
Agree a representative job and the acceptance criteria. Compare the output, turnaround, data requirements and total cost before deciding.
Available to evaluate on your own workload.
On the Azita fleet, or on an installation in your building.
We'll review what you need to run and contact you to discuss the right setup.
There is no price list. Your proposal states what is being quoted, the commitment and what is included. Human review, software licences and integration are listed wherever they apply.
Add what you pay for today. It travels with your enquiry as a note, so the comparison starts from the same work.
Prefer to read first? How pricing works
Your eval suite decides. We map each step to the smallest model that meets your pass criteria and run the suite on both stacks side by side. A step that does not pass stays where it is.
Send one verification pipeline with its eval set and last month's usage. We agree the pass criteria, run the suite on both stacks, and set out pass rates, latency and total cost for each step.
Your evals run in CI, and you cut over step by step behind your own flags. Any step that does not pass on the new stack stays with your current provider.
On the Azita fleet, or on an installation in your own building. Where your customer data is processed, who has access and how long anything is kept are agreed in your proposal before any work starts.
Proposal based on your workload and deployment. It states what is being quoted, the commitment and what is included, and lists human review, software licences and integration wherever they apply. There is no price list.
Term, what is included, exit and data handling at the end are set out in your agreement before you sign.
Related
Engineering and product
Agents, support, extraction and product features, tested on your own evals.
The page for every kind of work in this group, and how an evaluation works.
Read
Also for
Data extraction
Parsing, classification and field extraction on right-sized models, tested on your own documents. Compare accuracy, latency and total cost first.
Read
Also for
NBFC
Bank statement analysis, document verification and risk flags, evaluated on loan files you choose, with where the work runs agreed first.
Read
A production workflow and its eval set. We agree the pass criteria, then compare output, latency and total cost on the same input.
Arrange a workload evaluation