Observability & Evaluation
AI Agent Monitoring Platform
Monitors agent health, failures and drift in production.
Observability & Evaluation
AI Model Evaluation Platform
Multiple models and prompt versions are evaluated continuously over time, with a regression alert the moment quality drops.
Swapping a model or editing a prompt can quietly make your AI worse, and you often hear about it from a customer first. This platform scores your models and prompt versions against the same test cases on a schedule, across providers, and alerts you the moment quality slips below your threshold. Scores and history live in your own tooling, and rollback decisions stay with your team.
- Regressions caught when a model or prompt change lowers quality
- Side-by-side scores across OpenAI, Gemini, Bedrock and Azure OpenAI
- Usage, latency and cost tracked for each workflow
$6,900
20–30 working days
Optional maintenance $345/mo
What it is
AI Model Evaluation Platform runs ongoing evaluation across multiple models, providers and prompt versions, continuously rather than as a single benchmark run, and alerts you the moment a change causes quality to regress. It is built for teams comparing and swapping models over time, not a one-off quality check.
Why businesses buy it
Teams running AI in production change things constantly: a new model version, a cheaper provider, a reworded prompt. Without ongoing evaluation, each change is a guess, and a quiet drop in quality can sit in production for a long time before anyone connects it to a cause. This platform turns those guesses into scores you can compare over time, so model decisions rest on evidence. The written scope sets out which systems are covered, which monitors are configured and where alerts go, so you know what you are buying before the work begins.
Problems this solves
Swapping models or prompts quietly lowers quality without warning
The Evaluation Platform runs ongoing evaluation across models, providers and prompt versions. It alerts you when a change causes quality to regress, rather than waiting for complaints.
Comparing two models means building a new test every time
Evaluations run continuously against the same benchmarks, so models can be compared over time on equal terms. Up to three systems or AI applications are covered.
A one-off benchmark goes stale as providers update models
Because evaluation keeps running, results reflect the models as they are now. Up to five monitors are configured from your policies to flag the changes that matter.
A good fit if
You run more than one model or provider for the same task and need ongoing comparison, not a single point-in-time check.
You change prompts or swap model versions often enough that a one-off benchmark goes stale within weeks.
You need a regression alert the moment a model update or prompt change causes quality to drop, not a scheduled manual recheck.
You are accountable for output quality across several AI features and need one evaluation system tracking all of them over time.
Not the right fit if
You need a bounded, one-off benchmark for a single feature rather than continuous evaluation across models. See AI Evaluation System, our focused build for that.
You need a live view of latency, accuracy and error rate without the underlying continuous evaluation logic. See AI Model Performance Dashboard.
You need step-by-step tracing of one agent's reasoning, not evaluation of output quality across models. See AI Agent Observability.
Your project needs more than five evaluation configurations or a fully custom setup. Use our Custom AI enquiry form instead.
How it works
- We work with you to define the quality criteria and test cases that matter across your models, drawn from real examples, then set them to run on a continuous schedule.
- The platform is built vendor-neutral, evaluating outputs from OpenAI, Google Gemini, AWS Bedrock or Azure OpenAI side by side, on the same test cases.
- Every model version and prompt change is scored against the same baseline, so a regression is measured against a consistent standard, not a shifting one.
- When a score drops below your agreed threshold, an alert routes to Slack or a written report, identifying which model, version or prompt caused the regression.
- Historical scores are kept, so quality trends over weeks or months are visible, not just the latest run, which matters when a slow drift is easy to miss.
- We test the platform against your agreed scenarios, produce a test report, and hand over an admin guide plus a recorded session on reading trends and alerts.
What you provide within 72 hours
Your portal lists these the moment you order. Delivery starts the working day after everything is in and your access is checked.
- Your business information (company basics, hours and brand voice), shared during intake, or confirmation we can reuse what you gave us on an earlier order.
- The AI providers and API accounts the models being evaluated run on.
- Cloud or hosting access for wherever the evaluation platform will run.
- A technical owner who can define what counts as a quality regression.
- Written authorization for any testing against your live or sample data.
- Real examples of outputs, both good and bad, to build the baseline from.
- Admin access and API keys for every connected system, shared by adding our team as a user or creating a key you control, never by email.
- One decision-maker who can approve the final evaluation criteria and alert routing.
The 72-hour rule. Send everything on your checklist, including access, within 72 hours of ordering so your build starts on time.
Timeline
Start
business information confirmed and the models to be evaluated agreed.
Weeks 1–2
Evaluation criteria and baseline test cases built and connected to your chosen providers.
Week 3
Continuous scheduling and regression alert routing configured.
Weeks 3–4
Test report produced by running the platform against agreed scenarios.
Week 4
Your review and two rounds of changes to criteria or alert routing.
Go-live
Live, recorded handoff session, and the 30 days of support begins.
| Option | Delivery time | Price |
|---|---|---|
| Standard | 20–30 working days | $6,900 |
| Express | 15–25 working days | $7,950 |
| Rush | 10–20 working days | $8,950 |
What you receive at handover
- AI Model Evaluation Platform configured and deployed, evaluating across up to three systems or AI applications
- Ongoing evaluation across models, providers and prompt versions, with regression alerts
- Up to five monitors built from your policies, viewable in an admin console or written report
- A test report with a control test log for the agreed scenarios
- An admin guide and a recorded 60-minute handoff session
- 30 days of post-launch support
Expected benefits and how to measure them
- Can let you switch models with evidence rather than guesswork.
- Helps catch quality drops soon after a change.
- Keeps model comparisons current as providers update.
- Regressions caught before users noticed
- Count regression alerts and compare with quality complaints from users each quarter.
- Quality score per model and prompt version
- Track scores from the platform over time and compare before and after each change.
- Time to decide on a model switch
- Record how long the next switch decision takes, compared with the last one made without the platform.
Before you start: List the models and prompt versions in use and how they were chosen. Note recent quality complaints after a model or prompt change.
These are things to track, not promised results. Outcomes depend on your data, your team and your market.
Running costs
The build price is one-time. Running continuous evaluation afterwards costs roughly $20 to $300 a month in your own accounts, covering hosting plus a tool such as Langfuse that stores scores and history.
AI model usage for each evaluation run is also billed directly to your own provider accounts, so ownership of every provider relationship stays with your team.
Ask about running costsCustom requirements
If you need evaluation across more than three connected systems, or more than five evaluation configurations, add a note at checkout. You get a written Change Quote, and your original order keeps its normal timeline. Larger or bespoke projects use the Custom AI request form instead.
Request a custom versionKeep it running
Optional monthly maintenance covers monitoring, fixes, model and platform updates, a monthly health report and monthly change hours for new evaluation criteria or an added model as your lineup shifts. It starts after the 30 days of support and can be cancelled any month.
$345/mo (5% of the build price a month, includes 3 change hours)
Optional. Starts after the post-launch support period. Cancel any month.
How maintenance worksHow this compares
| Do it yourself with a SaaS tool | Hire a custom agency | Upmark Labs | |
|---|---|---|---|
| Price | An eval platform charges an ongoing per-model or per-run subscription | A custom continuous-eval build is quoted after discovery | Ours is one fixed price, shown on this page before you buy |
| Scope | An eval platform leaves you to define criteria and scheduling yourself | An agency agrees scope during the project | Ours is written to your models and criteria before you order |
| Delivery | An eval platform still needs real configuration before it runs usefully | An agency build usually takes several weeks, set per project | Ours has a fixed delivery time shown before you buy, with faster options |
| Nature | A generic eval tool may not alert on regression automatically | An agency deliverable depends on what was agreed | Ours runs continuously and alerts the moment quality regresses |
Questions about this product
How much does AI Model Evaluation Platform cost?
The build is one fixed price, and the panel on this page shows it with each delivery speed before you order. That price covers everything on the Scope Card: up to three AI applications in scope, up to five evaluations or monitors, and a report or admin console. Model usage for each evaluation run and the tooling that stores your scores are billed separately to your own accounts.
What does AI Model Evaluation Platform cost to run each month?
Running continuous evaluation afterwards costs roughly $20 to $300 a month in your own accounts, covering hosting plus a tool such as Langfuse that stores scores and history. There is no separate platform license on top of that figure. AI model usage for each evaluation run bills separately, directly to your own provider accounts.
How is AI Model Evaluation Platform different from AI Evaluation System?
AI Evaluation System is a focused, bounded build: a defined set of test cases scored once and rerunnable on demand for one feature. AI Model Evaluation Platform runs continuously instead, evaluating multiple models and prompt versions over time with automatic regression alerts, built for teams that need evaluation running constantly rather than periodically.
Can AI Model Evaluation Platform compare more than one AI provider at once?
Yes. The platform is built vendor-neutral, scoring outputs from OpenAI, Google Gemini, AWS Bedrock or Azure OpenAI against the same test cases and the same baseline. That side-by-side comparison, kept current over time rather than run once, is the core reason teams choose the continuous platform over a one-off benchmark.
What happens when AI Model Evaluation Platform detects a regression?
An alert routes to Slack or a written report, identifying which model, version or prompt change caused the score to drop below your agreed threshold. The platform reports the regression with the detail behind it; deciding whether to roll back a model or prompt change stays a decision for your own team.
Can we add models or change evaluation criteria later?
Yes. Adjusting an existing evaluation criterion or regression threshold usually fits inside the monthly change hours included with maintenance. Adding a genuinely new model to the comparison, or a fourth or fifth connected system beyond the three in scope, goes through a Change Quote agreed in writing before that work starts.
Can we cancel AI Model Evaluation Platform maintenance?
Yes. Maintenance has no lock-in, so you can cancel any month once the 30 days of included support has ended. It covers monitoring, fixes, model and platform updates and a monthly allowance of change hours, and anything bigger goes through a Change Quote.
Who owns the evaluation history AI Model Evaluation Platform builds up?
You do. Scores and evaluation history live in your own tooling, such as Langfuse, not a platform we control, so every trend and regression alert stays visible and editable by your team. We hand over an admin guide and a recorded session covering how the continuous scheduling and alerting work, with nothing locked to us.
Catch a quality regression the day it happens.
Order AI Model Evaluation Platform and continuous evaluation across your models is live on a fixed delivery date.
Works well with
Observability & Evaluation
AI Model Performance Dashboard
Compares model quality, latency and cost across workflows.
Observability & Evaluation
AI Evaluation System
Builds test sets and automated evaluations for your AI features.