Models
Reasoning, extraction, generation, multimodal understanding, and tool selection.
AI Benchmarks & Opinions
Test the capability, not the launch-day narrative.
We evaluate models and agents against business work: multi-step execution, browser and computer use, data access, reliability, and the operational cost of supervision.
Lambda × Aghata.io
Reproducible tests for business AI systems.
Methodology first
What every Lambda benchmark will disclose.
01
Task definition
The exact job, success criteria, inputs, and constraints.
02
Environment
Model version, tools, harness configuration, and evaluation date.
03
Reliability
Completion rate, repeatability, failure classes, and recovery behavior.
04
Human load
Setup, supervision, review time, and the expertise needed to trust the result.
05
Economics
Latency, token or infrastructure cost, and cost per successful outcome.
06
Verdict
Where the system is useful now, where it is not, and what would change our view.
Evaluation dimensions
The system around the model matters.
Agents
Planning, state management, retries, delegation, and long-running task completion.
Browser mode
Navigation, forms, research, structured extraction, and resilient web interaction.
Computer mode
Visual grounding and dependable operation across desktop applications.
Data access
Permission-aware retrieval, SQL and semantic search, freshness, and traceability.
Business intelligence
Turning operational data into explanations, decisions, and monitored action.
Reports in preparation
No scores before evidence.
We are standardizing Aghata.io's internal evaluation runs before publishing model comparisons. Subscribe for the first reports and direct opinions when the evidence is ready.
Benchmarked with Aghata.io
Aghata.io is Lambda's AI harness for browser, computer, and business-data workflows.
Get the benchmark brief.
New evaluations, practical criticism, and implementation notes—sent when there is something worth saying.