Make agent performance observable.
We turn consequential workflows into real-world evaluations: representative tasks, inspectable runs, scored artifacts, and decisions your team can defend.
Scope an evaluationReview warranty claims and update refund amounts
Review the attached warranty claims, then edit the existing product purchases spreadsheet to show the maximum refund amount a customer could receive for each product purchased.
Failure mode · Missed governing agreement constraints
GPT-5.5 · xhigh · Raycaster harness · public tier
Live public run · transcript · files · rubric
Inspect full run ↗Model-agnostic
Compare APIs, agents, vendors, or internal systems
Trace-level
See what happened between prompt and artifact
Built to persist
Reuse the suite for upgrades and regressions
Methodology
An evaluation is an evidence system.
A score without the task, run, artifact, and rationale is only a claim. Raycaster keeps the full chain connected so results are useful to engineers, domain experts, and decision makers.
Collect the work
Select representative tasks, source packets, tools, outputs, edge cases, and expert decisions—not idealized prompts.
Specify the judgment
Define what correct means at the claim, action, and artifact level. Make constraints, evidence, and review thresholds explicit.
Instrument the run
Capture prompts, tool calls, intermediate state, files, timing, cost, grader rationale, and final outputs in one comparable record.
Make the decision
Compare systems, inspect failure modes, set launch thresholds, and keep the suite running as models and workflows change.
What gets inspected
The trace explains the score.
Every published run above opens into the actual workspace: the prompt, transcript, tool calls, source files, edited artifact, grader evidence, cost, and timing. The proof is the product.
The engagement
A durable eval program, not a one-off report.
We combine evaluation engineering with domain review. Your experts define the work and judgment; Raycaster makes it reproducible, measurable, and maintainable.
Task suite
Versioned tasks and source packets sampled from the work that matters.
Evaluation harness
Reproducible environments, tool interfaces, and run configuration.
Rubric system
Deterministic checks plus expert or model grading where judgment is required.
Run corpus
Full traces, artifacts, scores, rationales, costs, latency, and failure labels.
Decision report
A deployment recommendation grounded in observable evidence.
Ongoing program
Regression gates and new tasks as the work, data, and systems evolve.
Reference harnesses
Products that keep the research honest.
We run our own document and spreadsheet agents through the same evaluation discipline. The product surfaces the hard parts; the benchmark makes them measurable.
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