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Overview

Decision Black Box (DBB) is a background reasoning agent in Membria for SMBs that automatically captures team decisions as they happen. DBB does not replace chat, workflows, or tools. It observes them and extracts decision signals from everyday work — conversations, documents, reviews, and approvals — turning ephemeral activity into institutional memory. For SMB teams, DBB solves a core problem:
important decisions happen constantly, but are rarely documented, tracked, or revisited.

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What DBB is (and is not)

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DBB is:

  • A non-intrusive background agent
  • Focused on decision capture, not summarization
  • Designed to work across multiple tools and sources
  • Always on, but rarely visible

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DBB is not:

  • A chat interface
  • A task manager
  • A monitoring or surveillance tool
  • A judgment or scoring system
DBB records what was decided, not who said what.

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How DBB works in a team environment

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1. Observation layer

DBB continuously observes team activity across connected sources:
  • Team chat (Slack, Teams, internal chat)
  • Documents and comments
  • Reviews, approvals, and status changes
  • AI-assisted outputs generated in Membria
At this stage, no reasoning or conclusions are produced.

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2. Decision signal detection

DBB looks for decision patterns, such as:
  • Explicit resolutions (“We’ll proceed with option B”)
  • Repeated convergence after discussion
  • Approval events
  • Rejected alternatives
  • Commitments tied to actions or owners
Signals are detected probabilistically, with confidence scores.

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3. Decision extraction

When confidence crosses a threshold, DBB extracts:
  • The decision itself
  • The context in which it was made
  • Key assumptions
  • Considered alternatives (if present)
  • Responsible parties (if identifiable)
  • Timestamp and source references
This extraction is structural, not interpretive.

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4. Persistence into the workspace SPL

Captured decisions are written into the workspace’s Smart Persistence Layer:
  • Linked to relevant documents and discussions
  • Connected to prior related decisions
  • Available to the Decision Surface and search
Once stored, decisions become part of the shared reasoning fabric of the team.

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Visibility and user experience

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Default behavior

DBB operates silently. Most of the time, teams do not interact with DBB directly. Its output surfaces indirectly through:
  • Decision Surface signals
  • Search results with provenance
  • Historical context in AI responses

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Optional review and correction

When needed, teams can:
  • Review captured decisions
  • Add clarifications or annotations
  • Mark decisions as outdated or superseded
Corrections do not erase history. DBB preserves the original capture and records updates as new events.

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False positives and confidence handling

DBB uses conservative heuristics to minimize noise:
  • Low-confidence signals are not persisted
  • Ambiguous discussions remain uncaptured
  • Long discussions without closure are flagged, not recorded
If a false positive occurs:
  • Teams can mark it as “not a decision”
  • DBB learns from the correction
  • Future confidence thresholds are adjusted

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Team governance and scope

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Workspace-level control

In Membria for SMBs:
  • DBB operates at the workspace level
  • All captured decisions belong to the team, not individuals
  • Access follows workspace permissions

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Escalation awareness

DBB is escalation-aware:
  • It records when AI escalation influenced a decision
  • It links decisions to escalated knowledge when applicable
  • It helps teams understand why certain answers were trusted

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Why DBB matters for SMB teams

Without DBB:
  • Decisions live in chats, emails, and meetings
  • Context is lost when people leave
  • Teams repeat mistakes or re-litigate old choices
With DBB:
  • Decisions persist beyond tools and people
  • New team members ramp up faster
  • AI responses improve using real team history
  • Institutional memory compounds naturally
DBB turns daily collaboration into durable knowledge — without adding process overhead.

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Relationship to Decision Surface

DBB feeds the Decision Surface. The Decision Surface shows:
  • Open decisions
  • Unresolved assumptions
  • Drift and contradictions
  • Historical outcomes
DBB captures. Decision Surface reveals. Together, they form the reasoning layer of Membria for SMBs.

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Summary

Decision Black Box enables SMB teams to:
  • Preserve decisions without manual effort
  • Maintain continuity across tools and time
  • Build shared reasoning capital
  • Reduce repeated discussions and hidden risk
DBB works quietly in the background, ensuring that what matters is never lost.