The AI features your product depends on, compared on your actual usage, so you see output quality and total cost before you change anything.
Prefer email? hello@azitalabs.com, subject “Workload evaluation: Founder watching burn”
Your product depends on AI features to attract users, and usage grows with every one you ship. Investors ask what each active user costs you, the vendors bill in dollars, and you cannot tell your product team to stop shipping. What you need is each feature's quality and total cost on your own requests, before the next board meeting.
An example workflow
Its writing assistant calls a frontier model every time a user pauses. An evaluation could run a sample of real requests through right-sized models and compare output quality, latency and total cost before the next fundraise.
An example workflow
Tutoring answers grow with every student it signs. An evaluation could take a sample of answered questions, agree the accuracy checks with the teaching team, and compare the answers and the total cost.
An example workflow
Contract summaries must be accurate, and customers ask where documents are processed. An evaluation could run a sample where customer terms allow and compare summary quality and total cost with the current provider.
The sample comes from real requests, and you decide what quality your users would notice.
Each AI feature is compared on its own requests, so you can move one and keep another where it is.
Each feature's total cost next to what you pay today, so the cost of every feature is visible before investors ask.
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
That is what the evaluation decides. You compare output on real requests against the answers you consider good. If a feature does not pass, it stays where it is.
Share the requests behind one feature and a month of usage. We agree what passes, run the sample, and set out output quality, latency and total cost side by side.
What is being quoted, the commitment and what is included, laid out before you sign. Integration and any human review are listed wherever they apply.
What can change the bill, such as additional volume or storage, is set out in your proposal before you sign, next to the commitment and what is included.
On the Azita fleet, or on an installation in your own building. Where your users' data is processed, who has access and how long anything is kept are agreed in your proposal before any work starts.
Term, exit and what happens to your users' data at the end are set out in your agreement before you sign.
Related
Finance and operations
The AI line item, compared on your own workload before anything moves.
The page for every kind of work in this group, and how an evaluation works.
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Also for
SaaS product
Routing and extraction steps behind your AI features on right-sized models, tested on your evals. Compare pass rates, latency and total cost first.
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Also for
CFO / finance head
Document processing, image generation and agent work, compared on a representative workload. See output quality and total cost before you decide.
Read
Send a redacted usage export. We agree a representative workload, then set out output quality and total cost side by side before you decide.
Arrange a workload evaluation