The platform

Built from the same parts as everyone else. Pointed at the one thing everyone else ignores.

NOW OS uses the same foundations as every serious AI system: frontier language models, agents, tool use, retrieval, a knowledge graph. The difference is where it starts. Everyone else starts with the machine and looks for work to give it. NOW OS starts with the work, models it from the whole institution down to the single act, and then decides what each act needs. That reversal is why NOW OS can shape your strategy instead of merely executing someone else’s.

The work model

Ten levels, from the institution to the single action.

NOW OS models work from the whole enterprise down to the smallest system-bound, sequenced, performer-bound step — the atomic action (for example, "grant read-only access to a system for 180 days").

The L0-to-L10 decomposition funnel, ending in the four AAA modes at the atomic action
L0 Institutional System → L1 Institution → L2 Mission Track → L3 Org Unit → L4 Department → L5 Role → L6 Area of Responsibility → L7 Master Task → L8 Sub-Task → L9 Task / Capability Item → L10 Atomic Action

The atomic action is the only level that carries a human-vs-AI designation. The placement is deliberate: a higher-level task is itself a mix of atomic actions, so stamping a single mode on it would flatten the signal. The parent task carries the mix — so for any task you can see how much is automatable, how much needs a human, and exactly where the boundary falls.

The scoring

Four modes. One written-down rule.

The scoring classifies each action by what kind of act it is and what it puts at stake, then applies a published threshold rule to derive an AI-Enablement level, a Trust Tier, and one of four modes. The rule is written down and identical every time — the same action always lands the same way, with a full trace of how it got there. Your people decide.

AutomateAI runs it end-to-end; humans audit out of band.
AugmentAI and human collaborate; humans review or approve at gates.
AssistAI gathers, drafts, and suggests; a human does the actual work.
Human-OnlyA person does it with no AI involved at all.
The scoring separates "can it run autonomously?" from "at what consequence?" — so two actions that are equally automatable can land in different modes purely because of stakes.

The platform explains why an action landed where it did — and distinguishes what it measured from what is expert judgment, rather than presenting both as the same kind of fact. The threshold values, the composition formula, and the policy floors are sealed NOW OS intellectual property.

The reasoning layer

A knowledge graph the system reasons over — not a document pile it retrieves from.

All facts live in a connected model of the organization — people, departments, policies, controls, tasks, and the relationships among them. Every answer fuses three layers, and silently invokes the right quantitative technique from a library of 49+ math, statistics, and ML capabilities.

Layer 1

Grounded facts

Retrieved from the organization's knowledge graph — with provenance on every borrowed fact.

Layer 2

Frontier reasoning

A leading AI model reasons natively on top of the graph — synthesis, inference, expert judgment.

Layer 3

Live external currency

Web search when law, regulation, or market facts need to be current — cited, never silently blended.

The agent estate

18 families. ~130 role-specialized agents.

Work is discovered, scored, governed, executed, and audited by named, role-specialized agents — not one copilot doing everything.

Cartographer

Discovers the work model from the organization's real corpus — tasks are found, not hand-authored.

Sentinel

Compliance and security: watches restricted work, flags violations, enforces the floors.

Weightsmith

Runs the scoring that places every action in its mode.

Skillbert

The conversational front end — guided intake that ordinary people can use on day one.

Librarian

Retrieval and citation — every claim traceable to its source.

Ledger

The auditor — a hash-chained record of every decision, re-verified on every read.

…plus analytics (Lens), recommendations (Advisor), workforce strategy (Strategist), and more. "Wired" is enforced, not asserted: every agent identifier must resolve to real executable code, and a build gate fails on any that doesn't.

Trust

An honest data path, end to end.

One governed lane in

Every fact that enters the live graph is validated against schema and contract before it is written, queued for a named reviewer, and re-validated on promotion. One path in, no side door.

Structural governance

NOW OS recommends; a named human decides; an advisory board governs; every decision is replayable from the ledger. Nothing auto-promotes — by construction, not by policy memo.

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