An independent AI lab
SV Future AI Labs builds AI-native tools for analysis. Agents do the work, every answer shows its sources, and people keep the judgment.
Thesis
The gap in AI analytics sits between the model and the decision: definitions, lineage, assumptions, and review. We build that missing layer, so agents can do analytical work a team can trust.
Own the question and the judgment. Review what the agent did before anything ships.
Runs analytical work end to end: plans the steps, cites its sources, flags its assumptions, and leaves a trail anyone can check.
Metric definitions, lineage, business rules, and past decisions, kept current and readable by both people and agents.
Claude, GPT, your warehouse, your BI. We work with what you already use.
How it works
Pick a question to see how an AI-native analysis runs: resolve the definition, trace the lineage, run the numbers, and flag what a person should check.
Illustrative example. Figures are made up.
Work
One product in the field, and a few experiments that may become the next one.
Product · Live
A working system for analytics teams that already use AI. It keeps definitions, data context, and decisions in one shared layer, so every new task starts from what the team already knows and every result can be reviewed.
analyticsharness.com ↗Experiment · Research
A plain-text format for metric definitions and lineage that any agent can read.
Experiment · Prototype
Benchmarks for whether an agent's analysis is correct, sourced, and honest about uncertainty.
Principles
We build from first principles and ignore the hype cycle. Silicon Valley spirit, on our own terms.
Claims come with evidence. An answer without its sources is a guess.
Analysis is a craft of small details. We sweat the definitions so the numbers hold.
Agents carry the work. People keep the judgment. We design for both.
Contact