OPTIMAIZE: EVIDENCE-BACKED OPTIMIZATION FOR AI AGENTS
Your agent may have hidden cost and latency.
Find out where.
Optimaize analyzes execution behavior across AI agent runs to uncover opportunities to reduce cost and latency, improve reliability, and simplify inefficient workflows.
Patent-pending AI agent optimization technology
01 Agent Execution Data
Traces across runs, models, tools, and routes
02 Big Data Analysis
Patterns, distributions, paths, loops, cost & latency
03 Optimization Intelligence
Bottlenecks, recurring behavior, architecture opportunities
04 Improved Agent Designs
Evidence-backed recommendations & workflow candidates
Re-optimize when technology evolves
Your agent can work, and still be inefficient.
Individual traces can tell you what happened during one execution. But many important optimization opportunities only become visible when behavior is analyzed across runs. Optimaize analyzes those patterns to determine where the workflow itself may be improved.
Rising model costs
Slow critical path latency
Repeated tools and LLM work
Excessive context propagation
Falling behind new agent techniques
Go beyond agent observability.
Observability tells you what happened. Logs, traces, dashboards, and evaluations help you understand individual agent executions and production behavior. Optimaize asks what should change.
Observe
Analyze
Improve
BIG DATA × AI
Modern agents generate increasingly complex execution data. A single trace may contain model calls, tool calls, branches, retries, loops, context transfers, and dynamically generated operations.
Across thousands or millions of executions, understanding that behavior becomes a data-analysis problem. Optimaize brings techniques from large-scale data systems together with AI-assisted analysis to turn patterns across agent executions into actionable optimization opportunities.
HOW IT WORKS
Optimaize aggregates execution behavior across runs, paths, workflow components, and dynamic regions to identify statistically and structurally meaningful optimization opportunities.
Recommendations are tied to evidence from your execution data rather than generic AI optimization advice.
01
Ingest
02
Normalize
03
Profile
04
Find
05
Recommend
New optimization patterns
Context reduction, routing, caching, batching, parallelization, and architectural patterns.
Agent-specific applicability
Optimaize evaluates techniques against the actual structure and behavior of your workflow.
Grounded recommendations
Only applicable changes become candidates, with expected impact, quality risk, and implementation requirements.
Human-in-the-loop adoption
Optimaize recommends and evaluates changes; your team decides which optimizations to adopt.
Have an agent running today? Let us analyze it.
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
Scail Labs is working directly with teams building AI agents and multi-step LLM applications. Share representative execution traces and we’ll analyze where your system may be spending unnecessary time, tokens, or computation — and where its workflow could be improved.
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
TECHNOLOGY / CREDIBILITY
Built for the next generation of AI infrastructure.
Optimaize is being developed by Scail Labs to apply large-scale execution analysis to increasingly complex AI-agent systems. Our work combines distributed-systems experience, big-data analytics, and AI-assisted optimization. Patent-pending technology.
Find out what your agent could improve.
Your agent already produces the evidence. We’ll help you turn it into optimization opportunities.
No migration required. Start with representative execution traces.