Most enterprises drown in dashboards and starve for decisions. Structuring hard choices — identifying the decision, framing scenarios, quantifying tradeoffs, and choosing a policy that can be explained and revisited — is a discipline with deep foundations in decision theory, operations research, simulation, reinforcement learning, and behavioral science. Decision Stack turns the discipline into a stack — a team of agents that propose options, run the math, and show their work. Between Knowledge Stack (what is true) and the action taken, Decision Stack is where judgment happens.
Decision Stack mirrors Knowledge Stack and Analytics Stack's four-layer architecture.
Infozense ships L1 and L2 — the assumption layer and the decision engine. L3 and L4 are your decision layer: bring your own, or start from our scenario templates and reference agents.
Each capability is delivered as an agent that helps strategists, operations researchers, and behavioral scientists.
Enumerates plausible futures — base, upside, downside, stress. Writes each scenario in plain language with its assumptions and probability.
Runs discrete-event or Monte Carlo simulations of each scenario. Reports distributions of outcomes with confidence bounds, not point estimates.
Solves LP, MIP, and convex problems. Finds the allocation, schedule, or portfolio that maximizes objective subject to your constraints.
Trains reinforcement-learning policies (PPO, SAC, behavioral cloning) inside simulated environments. Outputs a deployable decision rule.
Builds the Pareto frontier across competing objectives — cost vs speed, risk vs return, quality vs throughput. Makes the tradeoff visible.
Tornado diagrams and one-at-a-time analysis. Shows which assumptions matter — and which you can stop arguing about.
Discrete-event simulation with event graphs, priority-queue scheduler, and variance reduction. Python-native, reproducible, fast.
Versioned registry of every assumption — expert-elicited, data-calibrated, or scenario-stressed. Every decision traces back to a specific assumption set.
Applies Wendel's CREATE and DECIDE frameworks. When the decision is how humans behave, this is where ethics and design live.
Decision Stack runs anywhere and uses any LLM. Pick one option from each column.
Your cloud or on-premise. Full sovereignty over assumptions and decisions.
Best for: regulated industries and data sovereignty requirements.
We host, operate, and optimize it for you.
Best for: teams that want results without managing infrastructure.
Inference runs on your hardware. Assumptions and decisions never leave your boundary.
Best for: regulated industries, PDPA / BoT scope, data residency.
Inference runs on a vendor API — your guardrail inspects every request, redacts PII, and enforces data classification rules before anything leaves your boundary.
Best for: offloading specific tasks that exceed local-model capability — frontier-model power, used selectively.
