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CRM ⇄ AI

Gladly to Pinecone integration — real-time, two-way sync

Keep Gladly and Pinecone in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.

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Adopted by fast-scaling companies moving mission-critical data in real time

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Why teams connect Gladly and Pinecone

Write what Pinecone computes onto the contacts, accounts, and deals in Gladly, and feed Gladly's records back into Pinecone, in real time and in both directions.

Pinecone turns data into something a revenue team can act on: scores, classifications, summaries, and embeddings. But the customers those results describe live in Gladly, where reps and marketers actually work. Intelligence that stays inside Pinecone rarely reaches the record where a decision gets made, and Pinecone is only as sharp as the data it sees, which is also held in Gladly.

Stacksync connects Backups, Index statistics, Indexes, Vectors (records) in Pinecone to Conversation items, Agents, Topics, Tasks in Gladly with bi-directional, real-time sync. Records and fields from Gladly flow into Pinecone as the material it scores, indexes, or enriches, and the values Pinecone produces flow back onto the matching contact, account, or deal in Gladly, field by field, within seconds. There is no batch export in the middle and no glue code to maintain.

Because the mapping is field-level, you choose exactly which attributes cross and in which direction, so Gladly stays the record of the customer while Pinecone stays where the computation happens.

Common use cases

  • 01 Two-way sync vector metadata between Pinecone and an operational database so filters and tags stay aligned on both sides.
  • 02 Read an index's vectors and per-namespace statistics into a warehouse for auditing what is stored, sizing cost, and detecting drift from the source data.
  • 03 Sync Gladly customer profiles with an order database so agents see purchase history and profile updates flow back.
  • 04 Mirror conversations and topics into a warehouse for CX analytics and staffing models.

Common sync patterns

Where Pinecone enriches people or companies: fields fill in

Enriched attributes from Pinecone populate contact and company fields in Gladly, and refreshes keep them from going stale.

Where Pinecone scores or ranks records: results on the CRM record

Lead scores, fit ratings, or priority computed in Pinecone land as fields on the matching contact or account in Gladly, so reps sort and act on them without leaving the CRM.

Where Pinecone classifies or tags: labels sync onto the record

Categories, sentiment, or intent produced in Pinecone attach to the right contact, account, or deal in Gladly, keeping segmentation current as new data arrives.

What you can sync between Gladly and Pinecone

Representative objects on each side — any object or custom field can map to any target. Schemas are auto-detected; types are converted between the two systems.

Gladly objects Pinecone objects How this pairing syncs
Tasks Follow-up work items created from external triggers or synced for workload reporting. Namespaces Partitions inside an index; every read and write targets one namespace and vectors across namespaces are isolated. Enumerated with list_namespaces and sized per namespace via describe_index_stats. Tasks is specific to Gladly and Namespaces to Pinecone — each maps to any object or custom field on the other side.
Customer profiles The central entity; merges identifiers like email, phone, and order IDs, which syncs use for matching. Collections Immutable snapshots of a pod-based index that store its data but not its definition; created, listed, and deleted on the control plane and used to recreate a pod-based index. Serverless indexes use Backups instead. Customer profiles is specific to Gladly and Collections to Pinecone — each maps to any object or custom field on the other side.
Conversations Each customer's continuous timeline; status and outcomes sync to CRMs and warehouses. Backups Point-in-time snapshots of a serverless index; created, listed, and restored into a new index on the control plane for recovery or cloning. Read as a recovery-asset inventory. Conversations is specific to Gladly and Backups to Pinecone — each maps to any object or custom field on the other side.
Conversation items Individual messages across voice, SMS, chat, and email attached to the conversation. Index statistics Describe_index_stats returns total and per-namespace vector counts, the index dimension, and index fullness; read to size a sync and to detect drift between Pinecone and the source of truth. Conversation items is specific to Gladly and Index statistics to Pinecone — each maps to any object or custom field on the other side.
Agents User records used to attribute work in CX analytics. Indexes Serverless or pod-based containers holding vectors of a fixed dimension and distance metric (cosine, dotproduct, euclidean); managed on the control plane (api.pinecone.io) via create, list, describe, configure, and delete. describe_index returns the per-index data-plane host. Agents is specific to Gladly and Indexes to Pinecone — each maps to any object or custom field on the other side.
Topics Categorization applied to conversations; the key dimension for contact-driver reporting. Vectors (records) The core data: an id (up to 512 chars), a dense values array, optional sparse_values, and JSON metadata (up to 40 KB filterable per record). Full CRUD on the data plane via upsert, update, fetch, query, and delete, so write is supported here. Topics is specific to Gladly and Vectors (records) to Pinecone — each maps to any object or custom field on the other side.

How changes propagate between Gladly and Pinecone

Each direction of the sync is driven by what the source system can signal and what the destination accepts — detection, delivery, and expected latency below.

Gladly Pinecone Sub-second propagation

DetectionGladly notifies Stacksync of record changes through webhook events. Webhook event subscriptions for conversation and customer events, supplemented by polling and report exports.

DeliveryEach detected change is written to Pinecone through its API, with automatic retries and rate-limit backoff.

Pinecone Gladly Interval-based propagation

DetectionStacksync polls Pinecone for changes on an incremental schedule, reading only records changed since the previous pass. No webhooks and no native change-data-capture feed.

DeliveryEach detected change is written to Gladly through its API, with automatic retries and rate-limit backoff.

Rate-limit considerations

  • Gladly: Subject to the platform's API rate limits.
  • Pinecone: Data-plane operations are capped per second: query, upsert, update, and delete at 100 req/s per namespace, fetch at 100 req/s per index, and list at 200 req/s per index; breaches return HTTP 429. Hard request limits also apply: an upsert is max 2 MB or 1000 records, metadata max 40 KB per record, and query top_k up to 10,000 with a 4 MB result cap.
What ships with Gladly ⇄ Pinecone

Connect Gladly and Pinecone for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Gladly–Pinecone connection.

Real-time

Two-way sync

Changes in Gladly or Pinecone instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Gladly or Pinecone data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.

At scale

Event queues

Handle millions of events per minute without losing a single Gladly or Pinecone record.

Observability

Monitoring

Track your Gladly ⇄ Pinecone sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Gladly and Pinecone.

How the Gladly and Pinecone connectors work

Gladly

Integration surface
REST API
Authentication
API tokens used with basic authentication tied to an agent email
Change detection
Webhook event subscriptions for conversation and customer events, supplemented by polling and report exports
Capabilities
read · write · webhooks
Rate limits
Subject to the platform's API rate limits

Pinecone

Integration surface
Two HTTP APIs: a control plane at api.pinecone.io (manage indexes, collections, backups, and, via the Admin API, projects and API keys) and a per-index data plane at the host returned by describe_index (upsert, query, fetch, update, delete, list). A gRPC data-plane transport is available through the official SDKs.
Authentication
API key in the Api-Key request header, scoped to one project; every request also sends an X-Pinecone-Api-Version header (date-based, e.g. 2025-10). The organization Admin API instead uses OAuth2 client-credentials (service accounts) via login.pinecone.io/oauth/token, passing a Bearer token to api.pinecone.io/admin (Enterprise).
Change detection
No webhooks and no native change-data-capture feed. Vectors carry no server-side update timestamp, so Stacksync detects changes by re-reading - paginating vector ids with the list operation (serverless indexes) and fetching by id, or by re-upserting from the source of truth. describe_index_stats bounds a resync with per-namespace counts.
Capabilities
read · write
Rate limits
Data-plane operations are capped per second: query, upsert, update, and delete at 100 req/s per namespace, fetch at 100 req/s per index, and list at 200 req/s per index; breaches return HTTP 429. Hard request limits also apply: an upsert is max 2 MB or 1000 records, metadata max 40 KB per record, and query top_k up to 10,000 with a 4 MB result cap.
How it works

How to connect Gladly to Pinecone — three steps, no code

Configure and sync within minutes, no code. Whether you sync 50k or 100M+ records, Stacksync handles the queues, infra, and plumbing. Integrations are non-invasive and need zero setup on your systems.

  1. 01

    Connect your apps

    Authenticate Gladly and Pinecone with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.

    • OAuth 2.0
    • SSH tunnel
    • VPC peering
    Gladly connected
    Pinecone connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Gladly and Pinecone objects to sync — Stacksync auto-detects both schemas, including custom fields where the platform exposes them. Sync to existing tables, or let Stacksync create new ones with ideal data types.

    • Standard objects
    • Custom objects
    • Auto-schema
    objects · Gladly ⇄ Pinecone
    Customers 12,480
    Sales Orders 8,213
    Invoices 5,902
    Items 1,344
  3. 03

    Map fields

    Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.

    • Auto-map
    • Type casting
    • Transforms
    Gladly Pinecone
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
FAQ

Gladly and Pinecone integration FAQ

SECURITY

Security teams trust Stacksync

As a data company, we understand the importance of keeping your data secure. Stacksync is built with security best practices to keep your data safe at every layer, and is DPF-certified for US, EU, UK and CH data transfers.

SOC 2 Type II
ISO 27001
HIPAA BAA
GDPR
CCPA
DPF US-EU-UK-CH
→ SECURITY WITH BENEFITS

SSO & SCIM

Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.

Alerts

Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.

Secure connection options

Securely connects to your systems with:

Related integrations

Every pair below is a real-time, two-way sync. Search all 384 integrations available for Gladly and Pinecone.

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