Org rollups & dependency detection — “ENSEMBLE”
Org-wide rollup briefings, approval policies and cross-team dependency detection. The upmarket move into Ops and PMO, once decision-memory volume is real.
An ops lead evaluating write access to Gmail and Slack shouldn’t have to book a call to find out what Conductor can touch. The policy model, the audit record and the OAuth scopes are published below, along with what’s built, what’s planned, and in what order.
Decision execution infrastructure is the layer between a decision being made and the work it causes being tracked, owned, and done — with a policy check in front of every action and one record of who approved it, across every tool it touches.
“Guardrails” is a word every AI product uses. Here is what one actually looks like in Conductor. Policies are evaluated in the guardrail stage, which runs before execution — there is no code path to a tool that skips it.
A policy matches on the typed action, states what it requires, and states what it writes to the record. Nothing is inferred at runtime by a model, and nothing about a policy is a suggestion.
# external communication never fires on its own policy: external_communication matches: action.type in [gmail.send, slack.dm_external] requires: human_approval logs: actor, policy_id, decision, timestamp, directive_id # money gets a second signature above a threshold you set policy: spend_commitment matches: action.amount > 0 requires: human_approval, second_approver if amount > 5000 logs: actor, policy_id, amount, decision, timestamp, directive_id
This is the record that spans all four tools, and it’s the thing no single vendor’s agent can produce — because producing it means being neutral about the tool the action happened in.
The outcome field is also the scoreboard: approval rate is computed from it, per workspace, and it’s the number the eight-week design-partner phase exists to move.
Data handling. Workspace data is not used to train models. Decision embeddings are stored per workspace and are never queried across tenants.
Sanitise → triage → synthesise → guardrail → execute → learn. Unstructured intent in; typed, dependency-ordered, tool-executed actions out.
Per-workspace decision memory on pgvector with HNSW indexing. MCP-native protocol interface. Live execution in Linear, Slack, Notion and Gmail. The full mechanism is on the Product page →
Performance. Retrieval stays under 50ms at 10,000 stored decisions, so memory lookup adds no latency a user notices during triage.
Model cost runs around $0.0004 per directive. Noted for completeness; it isn’t a moat and it isn’t why anyone buys.
Internal codenames included because they’ll come up in diligence — with a plain-English name and an honest status on each.
The per-workspace store of every card, outcome and rationale. Live today in the core pipeline; the expansion adds retention analytics and cross-decision pattern detection.
Org-wide rollup briefings, approval policies and cross-team dependency detection. The upmarket move into Ops and PMO, once decision-memory volume is real.
A dry run of a directive’s full execution plan before anything is sent — what will be created, who gets notified, in what order.
Flags decisions that appear to be stalling — no owner confirmed, deadline slipping — before anyone has to ask.
Three further modules are in planning and deliberately unnamed here. Codenames for unbuilt software read as vaporware in diligence; these four get named because they’re sequenced and scoped.
Ship the core loop into five design partners matching the ICP. Instrument approval rate and decision-memory usage, not directives processed. Exit: a one-page proof showing approval rate over time. If the curve is flat, the memory thesis is wrong. This is what the $50,000 funds.
Approval policies, deeper guardrail configuration, and the decision-memory expansion (VAULT). Gated on the week-eight result, and on a seed round sized to it.
Org-wide rollup briefings and cross-team dependency detection (ENSEMBLE), gated on real decision-memory volume.
Pre-execution simulation (SIMULACRA) and proactive surfacing (PRECOG). SOC 2 and SSO are seed-stage work and sit in this window, not before it.
Integration reliability and the approval-rate instrumentation. The number the whole raise is buying has to be trustworthy before it’s useful.
Five workspaces, hands-on onboarding, weekly interviews. Free for the eight weeks; price set together afterwards.
Hosting, decision-memory stores, model spend, and the security review a 100-person company asks for on the first call.
Not funded by this raise: SOC 2, self-serve billing, multi-provider routing, and paid acquisition. Those are seed-round line items and they are out of scope until the curve exists.
Schema, policy engine, protocol layer — ask for the internals.