Built on PlantoOS

Meeting Decision Memory

Structured decision capture from meetings with task tracking and institutional memory continuity.

Why meeting decisions get lost

  • Critical decisions are buried in long conversations and unstructured notes.
  • Action items are inconsistently tracked across teams and systems.
  • Organizations lose historical context for why decisions were made.
  • Leadership lacks visibility into how decisions evolve over time.

What Meeting Decision Memory provides

Decision extraction

Convert meeting conversations into structured decision records.

Decision MemorySteering — Mar 10
active

Meeting Transcript

Steering Committee · Claims Automation Phase 2

14:32CTOWe should move claims triage to automation phase 2 this quarter.
14:33Ops LeadRollout starts in BFSI, pending policy validation.
14:35Risk Dir.I want a staged rollout — pilot first, then expand in Q3.

Extracted Decisions

DecisionOwnerStatus
Adopt phase-2 automation for claims triageCTOapproved
Set Q2 rollout window for BFSI pilotOps Leadapproved
Stage expansion pending pilot metricsRisk Dir.pending

Meeting Info

DateMar 10, 2026
Duration42 min
Attendees6
Decisions3

Task generation

Create follow-up tasks with owners, dates, and tracking context.

Decision MemorySteering — Mar 10
active

Generated Tasks

Auto-extracted from meeting decisions

OwnerTaskDueStatus
OpsDraft rollout plan for BFSI pilotMar 18pending
RiskValidate policy stack for automationMar 20pending
FinanceApprove pilot budget allocationMar 22pending
ITProvision staging environmentMar 24pending

Task Stats

Generated4
Assigned4
Completed0
Overdue0

Institutional memory

Store conversations as persistent organizational knowledge.

Decision MemorySteering — Mar 10
active

Institutional Memory

Decision timeline linked to strategy, budget, and policy artifacts

Decision Timeline

Jan 15Automation proposal loggedv1
Feb 08Risk review completed — conditionalv2
Mar 10Steering committee approvalv3

Linked Artifacts

strategy-doc.pdfbudget-q2.xlsxpolicy-stack-v3

Memory

Meetings14
Decisions38
Artifacts12
PeriodQ1 2026

Decision evolution visibility

Trace how strategic decisions evolve over time and reviews.

Decision MemorySteering — Mar 10
active

Decision Evolution

How this decision changed across reviews

Version Tree

v1

Initial Proposal

Full automation rollout for all verticals

v2

Risk-Adjusted

Scope narrowed — BFSI pilot only, phased expansion

v3

Approved

Pilot approved with Q3 expansion conditional on metrics

Change Summary

Rollout scope narrowed from org-wide to BFSI pilot before expansion. Risk-adjusted timeline added with quarterly checkpoints.

History

Versions3
Reviews4
Stakeholders6
Days to final54

Policy-bound agents

Capability enforcement ensures autonomous systems operate within explicit boundaries.

Governance Flow

Policy-bound agent execution ensures autonomous systems operate within boundaries.

Policy Layer
Agents
Capability Policies
Approved Tools
Enterprise Systems
Denied — policy block

Autonomous systems require explicit boundaries.

Where it sits in the stack

PlantoOS Architecture

The stack relationship between apps, agents, runtime, and systems.

Applications

Products and workflows

Agents

LLM-powered autonomous units

PlantoOS Runtime

Execution · orchestration · control

Capability Layer

Policy enforcement and tool access

Medhara Core

Memory · governance · lineage

Enterprise + Public Systems

Databases, APIs, infrastructure

A new compute layer for systems operated by agents.

Key workflows

How data flows through the system in typical usage patterns.

Workflow 1

Input

Meeting transcript and notes

Core Process

Extracts decisions, owners, deadlines, and rationale

Output

Structured decision artifacts and action list

Workflow 2

Input

Task follow-up cycle

Core Process

Tracks status changes and unresolved dependencies

Output

Operational visibility across decision execution

Workflow 3

Input

Historical decision query

Core Process

Recalls decision timeline and supporting context

Output

Institutional memory for better future planning

Measured outcomes

↓ 25–40%

Post-meeting admin overhead

↑ 20–35%

Task follow-through rate

↑ 30–45%

Decision context availability

Indicative ranges from internal benchmarks and early deployments; results vary by workload, model, and infrastructure.

How it integrates

SDK-first integration — governed from the first line of code.

1

Connect meeting feeds

Ingest transcripts and collaboration artifacts

2

Set extraction rules

Define decision and task capture templates

3

Sync downstream

Push structured outputs to task systems