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iGPT

iGPT: The context engine for work

Monthly visits
6.2K
Pricing
Freemium
Free, Pro, Team, Context Engine API
Added
Nov 03 2025

About iGPT

iGPT provides an AI-powered context layer that connects email, documents, and tools to produce reasoning-ready outputs for enterprise use. It is designed for teams and organizations seeking to turn conversations and files into actionable context for AI workflows. The platform emphasizes secure, governance-focused deployment and supports a unified access point for data sources and AI reasoning.

The product emphasizes integration and indexing of enterprise data. It presents a path from data ingestion to context shaping and reasoning, aiming to deliver outputs that are ready for automation and decision-making. It also highlights security features and access controls that govern who can see what data and results.

iGPT is positioned as a tool for building agents and copilots that operate with context from emails, attachments, and live web data. It describes a single API endpoint that performs retrieval, context shaping, and reasoning, reducing the need for multiple data access points and pipelines.

The enterprise offering discusses flexible deployment options and governance features. It notes cloud, hybrid, and fully private deployments, the admin console, and permissions that scale across teams and data sources. It also references compliance, audit trails, and zero data retention in certain configurations.

Use cases

  • Build agents that draft, prioritize, and act on email with full context.
  • Turn threads into tasks, deadlines, and approvals.
  • Reconstruct customer history across long email chains, attachments, and tone shifts.

Key features

  • SDK and live playground to test requests and responses quickly.
  • iGPT deeply indexes emails and attachment data automatically.
  • One unified endpoint that runs retrieval, context shaping, and reasoning in one pipeline.
  • Responses are ready for reasoning and automation, with citations to the source.
  • No parsing, chunking, indexing, or prompt tuning to maintain.
  • Realtime ingestion indexes new messages and attachments instantly.
  • Hybrid retrieval combines semantic and keyword methods with filters, scored and reranked in one call.
  • Thread reconstruction automatically rebuilds email threads across time, participants, and attachments.
  • Context shaping optimizes context windows for the LLM automatically; no prompt tuning.
  • Cited answers link back to source messages and attachments.
  • Unified endpoint replaces multi-endpoint retrieval with one natural language request across datasources.
  • Continuous data indexing keeps data and answers up-to-date with live indexing.
  • Permission-aware retrieval respects each user's mailbox scope; answers never surface content they can't access.

Pros and cons

Pros

Unified endpoint simplifies data access across sources.

Pricing

Free
$0
monthly
  • Context-aware AI for everyday work
  • CEF-Normal context reasoning
  • Ask, draft, brainstorm, and analyze with AI
  • Connect email datasource
  • Real-time web search with reasoning
  • Limits apply based on usage
Pro
$20
monthly
  • Everything in Free, with:
  • Powered by CEF-High
  • Connect full datasources stack
  • Higher usage limits
  • Faster responses during peak usage
  • Priority access to new capabilities
Team
$30
monthly
  • Everything in Pro, and:
  • Role-aware AI assistants and agents
  • Enterprise search across your org
  • Admin console for user and access management, central billing
  • Role-based permissions and access controls
  • Cloud, hybrid, or fully private deployment
  • SOC 2 Type II and full data encryption
Context Engine API
$1.10 / 1 M tokens (Input) and $6.50 / 1 M tokens (Output)
  • CEF-4 Normal
  • CEF-4 High
  • CEF-5 High
  • Live web search
  • No setup required

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Frequently asked questions

What is iGPT for enterprise?
iGPT for enterprise is an intelligence layer that connects your email, files, tools, and live web data, then turns that raw data into reasoning-ready answers with citations and structured outputs.
How is this different from enterprise search or “chat over docs”?
Search helps you retrieve, while iGPT reconstructs context. It identifies decisions, owners, risks, sentiment shifts, and next steps across threads and tools, then answers in a way that reflects how work actually unfolded.
Is our data used for training? Do you retain prompts or outputs?
No model training on customer data. For inference, the platform is designed for zero data retention, alongside enterprise controls and auditability.
What deployment options do you support?
Three models: cloud, hybrid, and on-prem. Cloud is fully managed. Hybrid keeps data in your VPC, while inference runs in the cloud. On-prem runs the entire platform inside your infrastructure.
Can we build custom agents for teams without engineering?
Yes. Teams can create custom agents with no code by selecting data sources, setting capabilities, and deploying internally. The same intelligence core powers chat, search, and agents across the organization.

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