What the integration will do in practice

Operationally, the integration will let a Peak Demand Voice AI session call Attio to read contact or company records, append notes or activity records, and create or update list/task-type items where your workspace schema supports them. For scheduling-like actions (for example, creating a calendar booking or task), the middleware validates the action model and will only issue writes if the Attio workspace and app scopes permit it.

• Read contact/company records to confirm identity or context.
• Write activity logs, notes, or other permitted record types.
• Create tasks/lists conditionally, subject to workspace model and app scope.

Integration boundary — what we will not assume

We will not assume universal write or scheduling privileges. The integration only does what the Attio app scopes and workspace permissions allow. Peak Demand does not claim built‑in Attio certification, guaranteed write access, or universal endpoint availability; those are determined by your Attio plan, workspace configuration and granted app scopes.

API classification and authentication

Attio provides a documented REST API and uses OAuth 2.0 for app authentication. Integrations use app scopes and must operate within workspace permissions. Your integration’s permissions are therefore explicit and granular at the app and workspace level.

• Public, documented REST API with OAuth 2.0 authentication.
• App scopes and workspace permissions restrict what an integration can access.

Capabilities supported by the official API

Per the official developer documentation, Attio’s API supports reading and writing records and subscribing to webhooks. What counts as a scheduling action is conditional — Attio’s model supports tasks and lists but whether a calendar booking or downstream scheduling is possible depends on how your workspace defines and permits those record types.

• Read: Yes — contact, company and custom records can be read.
• Write: Yes — records, notes and other writeable objects depend on scope.
• Webhooks: Yes — event subscriptions are supported.
• Scheduling/Tasks: Conditional — depends on workspace model and permitted record types.

Stepwise flow

1) A call arrives and the Voice AI captures intent and entities. 2) The middleware receives the action request, performs authentication (OAuth token management), validates payload schema and business logic, and checks scope/permissions. 3) If permitted, the middleware issues read/write requests to Attio. 4) Middleware records the result, returns a confirmation to the Voice AI, and logs the transaction for QA and audit. 5) If the action fails or requires human approval, middleware triggers escalation and places the task into the appropriate human review queue.

• Intent capture and entity extraction by Voice AI (on-premises or cloud model).
• Middleware enforces auth, validation and business rules before any write.
• Attio API reads/writes only after middleware permits the action.
• All actions produce durable logs and human-escalation paths.

Why the middleware matters in the flow

The middleware reduces risk by centralising token refresh, scope checks, validation against your CRM schema, rate-limit handling, and consistent logging, rather than embedding those responsibilities in the Voice AI session itself.

• Single control point for security and business rules.
• Deterministic logging for QA, analytics and audits.
• Simplified policy changes without re‑training the Voice AI.

Key middleware responsibilities

Authentication and token lifecycle management, payload validation against your Attio workspace schema, application of business rules (for example: read-only in after-hours, anonymize PII for test records), logging and analytics, retry and back-off for transient Attio API errors, and routing to human agents when required.

• OAuth 2.0 token storage and refresh (securely via a secrets manager).
• Schema validation and permission checks before issuing writes.
• Durable event logs and analytics export for QA and compliance.

Operational benefits of AWS specifically

AWS services (Lambda/ECS, Secrets Manager/KMS, SQS, CloudWatch/Observability stacks, and regioned data storage) provide predictable operational SLAs, secure key storage and the elastic capacity to handle spikes in call volumes. Use region selection, backup regions and subprocessors lists according to your data residency and support needs.

• Centralised observability and alerting.
• Secure secrets and encryption at rest and in transit.
• Elastic, queued operations to smooth peak activity.

Permissions, scopes and workspace model

Confirm which Attio app scopes you will grant and verify workspace permissions for the object types you need to read or write. If your use case requires task or scheduling items, confirm how those are modelled in the workspace and whether your app scope covers creation/updating of those objects.

• List required app scopes and confirm with your Attio administrator.
• Validate the workspace schema for task/list/calendar objects used in scheduling flows.

Operational prechecks

Confirm rate limits, webhook delivery semantics, data residency choices, and backup/region strategy. Confirm logging retention and whether call recordings or transcripts will be stored, and where. Review your legal and privacy obligations for recorded voice and personal data in the jurisdictions you operate.

• Rate limits and retry strategies affect near-real-time interactions.
• Webhook reliability and re-delivery behaviour must be part of your design.
• Validate data residency and onward-transfer implications with legal counsel.

Failure modes and safe defaults

Implement explicit fail paths: if an Attio write is rejected for permission, fallback to creating a read-only activity log in middleware and notify a human. If webhooks or network calls fail, queue the change for retry with exponential back-off and preserve the original context for human review.

• Rejection due to scope: create an internal incident or activity placeholder and notify operations.
• Transient API errors: queue and retry, with escalation after threshold.
• Invalid data: return a structured error to the Voice AI and prompt for human handoff.

Human handoff and QA

Where decisions require human judgement (complex scheduling conflicts, ambiguous identity verification, sensitive requests), the middleware should create a human review task in Attio or your ticketing system, include the call transcript and QA metadata, and notify the right cohort via existing channels.

• Attach transcript, intent confidence and extracted entities to the review task.
• Provide one-click takeover for agents to continue the call with context.
• Log all human interventions for compliance and QA sampling.