Rithmo Security & AI Data Privacy Whitepaper

Last updated: May 2026

Rithmo is an AI-enabled meeting governance platform designed for organizations that need more effective, accountable meetings without sacrificing control over sensitive business information.

Meetings often contain confidential customer discussions, internal strategy, product plans, financial information, legal analysis, personnel matters, security topics, and other high-value business context. Rithmo is built on the principle that AI can help organizations run better meetings only if meeting data is processed through clear boundaries, strong controls, and transparent vendor practices.

Rithmo’s security and privacy model is based on five core commitments:

Rithmo is not designed to avoid AI. Rithmo is designed to make AI use controlled, minimized, explainable, customer-scoped, and auditable.

This whitepaper explains how Rithmo protects customer data across its product architecture, meeting data lifecycle, AI processing model, vendor integrations, retention practices, and security controls.

It is intended for customer security, privacy, legal, procurement, and IT teams evaluating Rithmo for business use.

This document covers:

• customer data categories processed by Rithmo;
• live meeting and post-meeting processing boundaries;
• transcript, agenda, document, calendar, and derived meeting data handling;
• AI and external provider processing;
• tenant isolation and cross-customer contamination prevention;
• customer controls and administrative governance;
• access control, encryption, logging, retention, and deletion; and
• subprocessor and external service transparency.

This whitepaper should be read together with Rithmo’s Privacy Policy, customer agreement, Data Processing Addendum, and subprocessor disclosures.

Rithmo’s product is built around the following design principles.

3.1 Meeting Data Is Sensitive by Default

Rithmo treats meeting audio, transcripts, transcript segments, agenda content, uploaded documents, generated summaries, decisions, action items, recommendations, and behavioral analytics as sensitive customer data.

Meeting content is not treated as generic usage telemetry. It is customer business content and is protected accordingly.

3.2 AI Is Governed by Product Boundaries

Rithmo may use AI providers to support transcription, summarization, action item extraction, meeting assistance, recommendations, embeddings, text-to-speech, and other AI-enabled features. These providers are used through defined product pathways, not unmanaged employee workflows or ad hoc data movement.

3.3 Customer Data Remains Customer-Scoped

Rithmo is designed so that customer-specific meeting content, behavioral analytics, recommendations, memory, prompts, embeddings, and retrieval context remain scoped to the relevant customer, workspace, team, meeting, or authorized user context.

3.4 Sensitive Content Is Minimized Before External AI Processing

Rithmo’s AI processing model is designed to send only the minimum data required for a given task. When transcript or document content is needed for an AI feature, Rithmo uses bounded context, redaction, pseudonymization, identifier separation, and local rehydration controls to reduce unnecessary exposure.

3.5 AI Outputs Do Not Bypass Policy and Execution Controls

Rithmo separates AI-assisted decisioning from product execution. AI-generated insights, recommendations, and live meeting intents are routed through policy, validation, permission, and execution controls before becoming customer-facing actions.

Rithmo processes different categories of customer data, each with different sensitivity and handling requirements.

Rithmo provides two primary customer-facing experiences:

• an in-meeting experience for live meeting support; and
• a web dashboard for meeting preparation, review, analytics, settings, and follow-up workflows.

Behind these experiences, Rithmo uses a central application layer to coordinate meeting operations, transcript processing, agenda workflows, recommendations, integrations, analytics, and customer-facing updates.

The key architectural principle is controlled data flow. Rithmo’s product behavior is routed through defined application, policy, runtime, integration, storage, worker, and provider pathways. This reduces the risk of inconsistent data handling or uncontrolled automation.

Rithmo’s live meeting runtime is designed to keep customer-facing meeting behavior controlled and auditable.

A live meeting may involve inbound events from the meeting platform, meeting bot, transcript provider, user actions, agenda state, policy signals, and integrations. Rithmo normalizes those events, updates canonical meeting state through controlled paths, evaluates applicable policy and governance rules, and routes customer-facing actions through defined execution mechanisms.

This structure helps ensure that live meeting behavior does not arise from arbitrary model outputs or unmanaged automation. AI may assist the meeting experience, but customer-facing actions remain governed by Rithmo’s runtime, policy, validation, and execution boundaries.

Rithmo separates post-meeting analytics and learning from live meeting execution.

After a meeting ends, Rithmo may process transcript and meeting data to support summaries, decisions, action items, scorecards, recommendations, analytics, and customer-scoped learning.

The post-meeting layer is designed to:

• process transcript data after meeting completion and finalization;
• compute deterministic meeting, transcript, and participation signals;
• aggregate customer-scoped meeting behavior over time;
• generate insights and recommendations for future meeting improvement;
• support internal evaluation and product quality workflows; and
• prevent non-canonical analytics outputs from silently becoming live meeting behavior.

This separation allows Rithmo to learn from customer meetings while preserving clear boundaries between post-meeting analysis and live customer-facing execution.

Rithmo distinguishes between canonical product truth and supplemental AI-assisted analysis.

This boundary prevents Rithmo from creating competing sources of truth for the same customer-facing meeting outcome.

Rithmo uses AI and model-based services to support product capabilities such as:

• meeting transcription;
• summarization and recap generation;
• decision and action item extraction;
• agenda assistance;
• live meeting facilitation;
• document intelligence;
• semantic similarity and embeddings;
• recommendation generation;
• behavioral classification;
• meeting health scoring;
• text-to-speech; and
• evaluation and quality workflows.

AI processing is governed by the following controls.

9.1 Registered Product Purpose

Each external AI processing pathway is tied to a defined product purpose, such as summarization, facilitation, transcription, extraction, recommendation, embedding, or text-to-speech.

9.2 Minimum Necessary Data

Rithmo sends only the information needed for the specific feature. For example, a task that requires a short transcript window should not receive a full meeting transcript.

9.3 No General-Purpose Model Training

Rithmo does not use customer meeting content to train general-purpose AI models and requires external AI providers not to train their models on customer meeting content unless the customer expressly authorizes that use.

9.4 Contractual Vendor Controls

External AI, transcription, speech, infrastructure, and workflow providers are governed through contractual and technical controls appropriate to the type of service and data involved.

9.5 Content-Free Operational Logging

Rithmo’s AI usage logging is designed to capture operational metadata such as provider, model, task type, latency, success/failure state, and token usage where applicable, without storing raw prompts, raw transcripts, raw documents, or full model responses in routine operational logs.

Some of Rithmo’s core capabilities require processing transcript content. Rithmo’s security model does not depend on pretending transcript data is never used. Instead, Rithmo governs transcript use carefully.

When transcript content is processed for AI-enabled features, Rithmo applies the following controls:

These controls allow Rithmo to preserve core product capabilities while reducing unnecessary exposure of identifiable or sensitive meeting content.

Documents and attachments often contain highly sensitive business information. Rithmo treats uploaded or linked documents as high-sensitivity customer content.

Where document intelligence features are enabled, Rithmo may process document content to generate meeting preparation briefs, agenda context, document coverage analysis, participant-specific views, or other meeting-related outputs.

Document processing is governed by:

• explicit feature enablement;
• access controls tied to customer and meeting permissions;
• encryption for stored sensitive document artifacts where supported;
• external AI processing only where needed for the enabled feature;
• minimization and redaction before external AI processing where feasible;
• retention controls aligned to customer configuration; and
• audit logging that avoids raw document content in routine logs.

Enterprise customers may restrict document intelligence, require approved providers, or use stricter processing configurations based on their security requirements.

Rithmo is designed as a customer-scoped platform. One customer’s meeting content is not used to generate customer-facing outputs for another customer.

This principle applies to:

• prompts;
• summaries;
• recommendations;
• meeting memory;
• embeddings and retrieval context;
• caches;
• behavioral learning records;
• profile and signature records;
• analytics; and
• customer-facing output generation.

Rithmo’s tenant isolation model is designed around customer-scoped storage, permission-checked retrieval, scoped prompt context, scoped caches, scoped embeddings, and customer-specific learning boundaries.

Rithmo is designed to give customers control over how meeting data and AI features are used.

Depending on the customer’s plan and enabled features, administrators may control:

• whether Rithmo is enabled for particular meetings, teams, or workspaces;
• whether transcription is enabled;
• whether AI-generated summaries, decisions, action items, recommendations, and live facilitation are enabled;
• whether document intelligence is enabled;
• which integrations are connected;
• which users and roles may access meeting outputs;
• retention settings for transcripts, outputs, analytics, documents, and logs;
• stricter handling for sensitive meeting categories; and
• whether customer content may be used for optional product-improvement programs.

Customer administrators are responsible for configuring Rithmo in accordance with their organization’s internal policies, participant notice requirements, and applicable law.

Rithmo uses third-party providers to operate the service and provide customer-enabled features. Provider usage depends on the customer’s configuration and the features enabled.

Rithmo maintains subprocessor disclosures that identify providers, processing purposes, and data categories applicable to the Rithmo service.

Rithmo uses a layered access model.

15.1 Standard Users and Meeting Participants

Standard users and meeting participants may access only the meetings, outputs, and workflows authorized by the customer’s configuration and their role.

15.2 Customer Administrators

Customer administrators may have broader visibility within their own organization, including settings, integrations, reporting, analytics, retention controls, and meeting history, depending on the customer’s configuration.

15.3 Rithmo Operational Access

Rithmo operational access to customer content is restricted to authorized personnel with a legitimate business, support, security, or legal need. Operational access is governed by least privilege, access controls, and auditability.

Customers should not assume that all Rithmo personnel have broad default access to sensitive meeting data.

Rithmo uses technical safeguards to protect customer data in transit, at rest, and during integration workflows.

16.1 Encryption in Transit

Rithmo uses HTTPS/TLS-based communications for user-facing application traffic and external provider connections.

16.2 Encryption at Rest

Rithmo uses storage-layer encryption for databases, object storage, backups, and infrastructure services where applicable, and application-layer encryption for selected high-sensitivity data classes.

16.3 Application-Layer Encryption

Application-layer encryption may be used for high-sensitivity data such as:

• calendar integration tokens;
• meeting-platform OAuth tokens;
• internal agenda content;
• document artifacts;
• uploaded meeting attachments;
• generated document briefs; and
• other high-sensitivity content.

16.4 Credential and Token Protection

OAuth tokens, session secrets, API keys, and integration credentials are protected through encryption, hashing, limited access, and secure storage practices appropriate to the credential type.

Rithmo uses structured logging and audit-oriented architecture to support reliability, security, troubleshooting, customer diligence, and incident response.

Operational logs are designed to capture information such as:

• request identifiers;
• customer, organization, team, or meeting scope;
• task type;
• provider and model information;
• latency;
• token count where applicable;
• success or failure state;
• fallback usage;
• feature flag state;
• redaction status where applicable;
• retention mode where available; and
• policy or guardrail outcome.

Rithmo does not store raw transcripts, raw documents, full prompts, or full model responses in routine operational logs. Any elevated debugging or support workflow involving sensitive content is access-controlled, time-limited, and governed by support, security, and customer-authorization controls.

Rithmo’s retention model distinguishes between raw meeting content and longer-lived customer value.

Upon customer termination or verified deletion request, Rithmo deletes or returns customer data according to the applicable customer agreement, legal obligations, product capabilities, and backup deletion cycles.

Rithmo’s security model supports a structured incident response lifecycle:

1. Detect and triage suspected security events.
2. Investigate using audit trails, logs, provider telemetry, and system metadata.
3. Contain affected systems, credentials, integrations, or workflows.
4. Remediate the issue and validate corrective action.
5. Communicate with affected customers where required by contract, law, or incident severity.
6. Improve controls based on lessons learned.

Incident notification timelines and contractual commitments are governed by the applicable customer agreement or Data Processing Addendum.

Rithmo supports enterprise diligence through a set of customer-facing security and privacy materials, which may include:

• Privacy Policy;
• Data Processing Addendum;
• subprocessor list;
• AI processing summary;
• retention summary;
• security architecture overview;
• incident response summary;
• access control and privileged access summary;
• encryption and key management overview;
• vendor data protection commitments;
• data residency and hosting information where applicable; and
• security assessment materials where available.

These materials are intended to help customers evaluate Rithmo’s data protection posture without relying on broad marketing claims.

Rithmo helps organizations use AI to improve meeting governance while preserving control over sensitive meeting data.

The platform’s security and privacy posture is based on:

• controlled live meeting runtime paths;
• separation between live execution and post-meeting learning;
• customer-scoped analytics and recommendations;
• AI processing through defined provider pathways;
• transcript and document minimization;
• no general-purpose AI training on customer meeting content;
• tenant isolation;
• customer controls;
• retention and deletion practices; and
• auditability.

Rithmo’s goal is to make AI-assisted meeting governance practical for enterprise customers by ensuring that AI use is transparent, purpose-limited, contractually governed, minimized, and customer-scoped.