For Data & ML Teams

Ship the experiment. Then prove it worked.

Every prompt change, every model swap, every new fine-tune: how do you know it was an improvement? Oculis gives data and ML teams real-time A/B comparison with cost, latency, and quality deltas — so you ship with evidence, not hope.

“Which model wins — and at what cost?”
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What You'll See

Three experiments, three answers.

The views ML teams actually reach for during a model migration or prompt tuning run.

01

A/B model comparison

Run two models on the same traffic. See cost, latency, and quality-score deltas in real time. Stop experiments early when the answer is obvious.

  • Traffic split: 50/50, 90/10, or whatever you need
  • Cost delta in dollars, not percentages
  • Latency percentiles side by side
  • Statistical significance indicators
experiment-042 · prompt-v3 running · 18h
Agpt-4-turbo
Cost / run$0.124
p95 latency2.8s
Quality4.2
vs
Bclaude-haiku
Cost / run$0.018−85%
p95 latency1.1s−61%
Quality4.1−2%
95% confidence B winning on cost & latency, quality within noise. Ship B?
02

Prompt quality scoring

Tag runs with quality signals — eval scores, user ratings, downstream conversion — and see which prompt templates are actually winning.

  • Score every run with a number you choose
  • Group by prompt template or prompt version
  • Correlate quality with cost — find the high-value prompts
Prompt templates · quality vs. cost
summarize-v2
Quality
4.6
Cost
$0.02
classify-v4
Quality
4.0
Cost
$0.01
draft-v1
Quality
2.1
Cost
$0.44
draft-v1 is expensive and low-quality — deprecate or rewrite.
03

ROI per experiment

Every prompt change, every model swap, every fine-tune — get a clear dollar-denominated result so you can defend the effort to leadership.

  • Before / after metrics auto-captured at experiment boundary
  • Projected annual savings if you ship the change
  • Export experiment history to Notion, Jira, or your doc tool
experiment-042
prompt-v3 · gpt-4 → claude-haiku · 14 days
Shipped
Cost per 1k runs
$124
→
$18
Projected annual savings
$5,040
What You Can Do

Experiment with accountability.

Four outcomes Oculis delivers for data and ML teams.

Run real A/B tests

Traffic-split experiments with live cost and quality deltas. Stop early when the winner is obvious.

Defend your model choice

Show leadership why you picked claude-haiku over gpt-4. Numbers, not vibes.

Find prompt wins fast

Discover which prompt templates are high-quality and low-cost — and which should be rewritten.

Export to your toolchain

Experiment history in Notion, Jira, or Linear. ROI math in a Google Sheet. Data lives where your team works.

Related Capabilities

The platform pieces that matter for you.

Go deeper on the features most relevant to experimentation.

04

Multi-Model Support

Every provider, every model, normalized for fair comparison.

→
03

Run Analytics

Full-text search across every prompt and response.

→
02

Cost Intelligence

Dollar-denominated cost per run, per agent, per experiment.

→
Ready?

Experiment with evidence.

30-minute demo. Bring an experiment you're running today — we'll show you what Oculis would have surfaced.

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