Evaluation environments · Data · Research
Where agents prove they can do real work.
Raycaster builds the data, environments, and evaluations required to make AI agents reliable at consequential professional work—with tasks, tools, trajectories, artifacts, graders, and expert judgment.
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Failure mode · Missed governing agreement constraints
GPT-5.5 · xhigh · Raycaster harness · public tier
Live public run · transcript · files · rubric
Inspect full run ↗Domain and workflow
What work matters to you?
Choose an industry. We’ll point you to the most relevant public examples and the right next conversation.
Beyond fickle chat tools
The proof is the published run above—not a demo.
Generic assistants improvise. Raycaster shows inspectable tasks, trajectories, artifacts, and criteria—including failures—so deployment decisions and expert judgment rest on evidence.
How experts contribute →Benchmark catalog
Evaluate the work, not the demo.
Benchmark / documents
OfficeQA
Agents that must find, reason over, and act on evidence across realistic workplace files.
Open benchmark ↗Benchmark / spreadsheets
SpreadsheetBench
Spreadsheet tasks scored on the finished artifact—not a plausible-looking chat response.
Open benchmark ↗Benchmark / agents
APEX-Agents
Long-horizon tasks that expose tool use, recovery, and end-to-end completion.
Open benchmark ↗What Raycaster builds
One evidence chain, from task to verdict.
We capture representative professional work, reconstruct it as reproducible agent environments, evaluate complete trajectories and finished artifacts, and use that evidence to improve systems and help organizations deploy them.
Benchmark data
Tasks, source packets, rubrics, and expert judgments drawn from work people actually do.
Evaluation infrastructure
Reproducible harnesses, full traces, artifact inspection, graders, and comparable run records.
Cloud agents
Workspace products that perform the work being evaluated—so research stays honest and teams can automate file work in the same harness.
Choose a path
How do you want to work with Raycaster?
Choose evaluate, build, or contribute—we’ll take you to the right conversation.
Evaluate a workflow
Private evaluation before you deploy—clear tasks, scoring criteria, and inspectable runs for your work.
Request an evaluation 02Build data & environments
Expert data and realistic work environments for training and evaluating agents on hard professional tasks.
Talk about a project 03Contribute expertise
Practitioners and specialist firms help shape evaluations from real work—without becoming a labeling gig.
Explore contributionPrivate evaluations
Turn your hardest work into an eval.
We work with your experts to capture representative tasks, encode the rubric, run candidate systems, and leave you with a durable evaluation program.
Cloud products · same harness
Automate file work. Keep a record the eval can score.
Workspace is where people run agents on documents and spreadsheets. Eval is where those runs stay inspectable. One harness, two surfaces.
Start with evidence
Bring us work an agent needs to get right.
We will make it reproducible, measurable, and improvable—and show the evidence.
Talk to Raycaster