Trace every decision — human or AI — back to facts you can defend.

DecisionFacts is the interoperable layer underneath your agents and simulations, keeping every decision — a robot's next move, a fraud block, an inventory reorder — inside the policy boundary you set.

Every decision, traced back to its facts.

Decisions used to be a moment. Now they're a stream.

Toggle to see what changed.

Before agentic AI In the agentic era
Data
Human judgement
Decisions
Problem: Human expertise, limited scenarios, time to take action.

DecisionFacts gives AI models the intelligence for higher-order autonomous decisions.

Real data, tested in simulation, evaluated before it acts — and every action becomes tomorrow's data.

Outcomes become tomorrow's facts. Generated Data Interoperability Simulation Harness Training Interoperability Evaluation Harness Action Auditability First-party data Structured & unstructured Third-party data

Grounded in first-party & third-party data

Generated Data

Interoperability

Simulation

Harness

Training

Interoperability

Evaluation

Harness

Action

Auditability

↻ Outcomes become tomorrow's facts.

Weigh a wide range of scenarios before acting — without infrastructure complexity getting in the way.

See it running.

app.decisionfacts.ai
Integration panel showing connectors for Salesforce, Jira, MongoDB, Azure, Deepseek, and other data sources and models, alongside code calling multiple LLM providers through one interface

Connect anything — Salesforce, MongoDB, any LLM — without rebuilding your integration layer.

What makes autonomy defensible.

Take one away, and either speed or trust breaks down.

Interoperability Any cloud, any model, any framework — one interface.
Compute Storage Databases & RAG Containers Any LLM Any cloud
Auditability Every input and output traced, from training data to the decision it produced.
Multi-agent orchestration Custom APIs Batch scenarios Logging & audit trail
Harness Intent becomes a policy framework that holds the boundary and flags risk.
Simulations Policy guardrails Model fine-tuning Workflow orchestration

Built for the AI you're running today — and the AI that's coming.

Same platform. Same three pillars. Agentic, physical, or enterprise-scale — the requirements don't change.

Defensible by default

Every decision comes with the evidence trail a regulator or board will ask for.

Continuous, goal-driven execution

Agents keep working toward the outcome you define — catching errors humans miss, and humans catch what automation misses.

Scale without adding headcount

Agents handle the volume; your team handles the exceptions that matter.

Lower operational risk

Guardrails catch unintended consequences before they become costly.

Agentic AI

Agents will make more decisions than people do. The question isn't whether they're fast — it's whether every one traces back to a fact.

Physical AI

When the decision is a robot's next move, there's no undo button. Simulation and hard guardrails stop being optional.

The next enterprise

Operations won't route through a dashboard someone checks each morning. They'll run continuously, with humans reviewing the exceptions.

Grounded in published research.

“Collaboration in DecisionFacts helps us do analysis faster.”

VP of Supply Chain, publicly traded NYSE biotech company, CA

“Before DecisionFacts, it was difficult to compare new code, parameters with old data or vice-versa. This delayed business acceptance of new models. Now, built-in tracking of DecisionFacts becomes the system of engagement.”

Ram Krishnamurthy, Co-Founder, CoveLabs.ai, NC

150M+
scenario simulations run
200K+
documents extracted & indexed
25K+
hours of computation

Why we built this.

Our mission is to help enterprises adopt agentic and physical AI without giving up control — turning institutional expertise into a governed platform where every decision, autonomous or human, can be trusted and defended.

Our team brings more than 40 years of combined experience across cloud infrastructure, analytics, AI/ML, supply chain, and finance — the same disciplines now converging in agentic and physical AI. We've spent that time building systems where getting a decision wrong has a real cost: manufacturing lines, financial transactions, supply networks. That discipline is what's built into DecisionFacts — by people who've had to defend a model's decision to a regulator, a board, or a plant manager, now applying it to the agents and robots making decisions next.

We're a global team, with roots in the Bay Area, California and Chennai, India.

Plug and Play logo Recognized Top 10 of 500+ startups in the Plug and Play Enterprise Tech cohort
AICPA SOC for Service Organizations certification badge Compliant SOC 2 Type II — independently audited data handling & security
NVIDIA Inception Program logo Member NVIDIA Inception Program

Questions? info@decisionfacts.io

Wherever you're starting from, we can help.

Whether you need data to build models, generate data for robotics and vision-language model training, or train the models themselves — we'll be happy to assist you in your journey.

Contact us at info@decisionfacts.io