CRM Basic Authentication

Sync Insightly CRM Data to Flat Files & Spreadsheets

Insightly CRM

Automatically sync your Insightly CRM data to cloud storage and spreadsheets with Flatly's no-code, triggerless, turnkey integration service.

Historical & Dynamic Data
One-way Sync
For Non-technical Users

About the integration: Insightly is a SaaS-based CRM solution targeted at small and mid-sized businesses. Flatly integrates with Insightly CRM's official APIs.

Available Datasets

Flatly can sync the following datasets from Insightly CRM.

  • ActivitySets
  • Contacts
  • Contacts+Details Combo
  • Contacts+Emails Combo
  • Contacts+Events Combo
  • Contacts+FileAttachments Combo
  • Contacts+Links Combo
  • Contacts+Notes Combo
  • Contacts+Tasks Combo
  • Countries
  • Currencies
  • CustomObjects
  • CustomObjects+Records Combo
  • Emails
  • Emails+Comments Combo
  • Emails+FollowRecords Combo
  • Emails+File Attachments Combo
  • File Categories
  • Follows
  • Leads
  • Leads+Details Combo
  • Leads+LinkEmailAddresses Combo
  • Leads+Emails Combo
  • Leads+Events Combo
  • Leads+FileAttachments Combo
  • Leads+Links Combo
  • Leads+Notes Combo
  • Lead Sources
  • Lead Statuses
  • Leads+Tasks Combo
  • Milestones
  • Notes
  • Notes+Comments Combo
  • Notes+FileAttachments Combo
  • Opportunities
  • Opportunities+Details Combo
  • Opportunity Categories
  • Opportunities+Emails Combo
  • Opportunities+FileAttachments Combo
  • Opportunities+Follows Combo
  • Opportunities+Links Combo
  • Opportunities+Notes Combo
  • Opportunities+StateHistory Combo
  • Opportunities+Tasks Combo
  • Opportunity State Reasons
  • Organisations
  • Organisations+Details Combo
  • Organisations+Events Combo
  • Organisations+FileAttachments Combo
  • Organisations+Follows Combo
  • Organisations+Links Combo
  • Organisations+Notes Combo
  • Organisations+Tasks Combo
  • Pipelines
  • Pipeline Stages
  • Price Books
  • Products
  • Project Categories
  • Projects
  • Projects+Details Combo
  • Projects+Emails Combo
  • Projects+Events Combo
  • Projects+FileAttachments Combo
  • Projects+Follows Combo
  • Projects+Links Combo
  • Projects+Milestones Combo
  • Projects+Notes Combo
  • Projects+Tasks Combo
  • Quotes
  • Relationships
  • Task Categories
  • Tasks
  • Tasks+Details Combo
  • Tasks+Comments Combo
  • Tasks+Links Combo
  • Teams
  • Team Members
  • Tickets-Alltime
  • Tickets-Last X days Date-ranged
  • Tickets+Details-Alltime Combo
  • Tickets+Details-Last X days Combo Date-ranged
  • Tickets+Comments-Alltime Combo
  • Tickets+Comments-Last X days Combo Date-ranged
  • Users

Send Insightly CRM data to

Flatly can sync Insightly CRM data to any of these destinations.

Note: Some destinations are aliased, for all intents and purposes they are functionally equivalent.

Querying Insightly CRM - AI or ETL?

Many SaaS applications and databases can be directly queried within AI chat apps using connectors. For ad-hoc, single-user requests, this direct architecture is superior—it offers real-time visibility, high customizability, and bypasses the need for complex data pipelines.

However, ETL (Extract, Transform, Load) can be more favorable when certain requirements exist. You might consider transitioning to an ETL system and a centralized data store when:

  • Collaboration is required: Multiple stakeholders (colleagues, partners) need consistent access to the same shared single source of truth.
  • Downstream audiences: The queried data must be routed into other internal IT systems, published to team dashboards, or preserved in official records rather than remaining isolated in a chat window.
  • Data is complex: The raw data needs heavy cleaning or joining before an AI or non-technical user can accurately understand it.
  • Internal capabilities are limited: Your organization lacks the in-house programming resources or infrastructure necessary to reliably build, deploy, and maintain custom agentic workflows or complex data integrations from scratch.
  • Numerous accounts: When a high volume of identities or accounts within a data source need to be analyzed in bulk, a sophisticated connection manager is needed.
  • Concurrency & infrastructure: If many data sets need to be analyzed in parallel, concurrency can become an issue. The device hosting an AI agent can become saturated without concurrency controls in place, whereas an ETL pipeline is built to handle parallel workloads reliably.