OPTIMAIZE BY SCAIL

Is your AI agent costing more than expected?

Is your AI agent costing more than expected?

Rising model costs, slow response times, repeated work, excessive context, and unreliable execution can all indicate workflow inefficiencies. Selected organizations can partner with Scail for a complimentary real-world evaluation using Optimaize.

Rising model costs, slow response times, repeated work, excessive context, and unreliable execution can all indicate workflow inefficiencies. Selected organizations can partner with Scail for a complimentary real-world evaluation using Optimaize.

01

Agent Traces

Sanitized execution paths

02

Analysis

Cost, latency, retries, context

03

Evidence

Findings tied to steps

04

Recommendations

Practical next experiments

Agent inefficiencies are difficult to see

Observability may show what happened. Optimaize is designed to identify what could be changed—and connect each finding to specific steps in the workflow.

Rising model costs

Slow critical-path latency

Repeated tools and LLM work

Excessive context propagation

Evidence-backed agent evaluation

Optimaize analyzes execution traces and connects findings to the specific steps that create cost, latency, reliability, and workflow risk.

Cost and token analysis

Latency and critical-path analysis

Retry and failure analysis

Context propagation analysis

Duplicate-work detection

Workflow candidate generation

How the design partnership works

01

Provide representative, appropriately sanitized agent traces

02

Scail analyzes the workflow using Optimaize

03

We review evidence-backed findings together

04

Where practical, we measure selected improvements

This is a joint technical evaluation, not an open-ended free consulting engagement.

What participating teams receive

• Baseline cost, token, latency, retry, and reliability analysis
• Workflow visualization
• Prioritized evidence-backed recommendations
• Potential workflow candidates
• Review of expected impact, quality risk, and implementation effort
• Before-and-after comparison when selected changes can be tested

Who is a good fit?

• Has a working AI agent or multi-step LLM workflow
• Can provide representative sanitized execution traces
• Has measurable task outcomes
• Has an engineer available to explain the workflow
• Is open to testing and providing feedback on recommendations

TRANSPARENCY

What we are validating

Optimaize is currently being tested on real-world systems. Workflow candidates may initially be structurally validated or estimated rather than production-executed. Recommendations depend on trace completeness, and no cost, latency, or quality improvement is guaranteed.

Apply for a complimentary agent evaluation

Scail is selecting a limited number of design partners for joint technical evaluations.

Thank you. We’ll review your application and follow up if there’s a fit for the current evaluation cohort.

Scail

Optimaize by Scail

Evidence-backed evaluation for real-world AI-agent workflows.

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