Agora vs Glean: Which Enterprise AI Search Platform Fits Your Organization?

Why This Comparison Matters

Enterprise AI search has become a critical layer in how modern organizations operate. The ability to surface relevant internal knowledge, automate repetitive tasks, and deploy intelligent agents across teams can mean the difference between 1.8 hours of wasted search time per employee per day and instant answers.

Both Agora and Glean address this problem. But they take fundamentally different architectural approaches that affect your long-term flexibility, data sovereignty, and total cost of ownership.

This comparison is designed to help engineering leaders, CTOs, and infrastructure teams make an informed decision based on technical reality, not marketing.

At a Glance

Capability	Agora	Glean
Deployment	On-premises, private cloud, managed cloud	Cloud-only (customer-hosted cloud at best)
Air-gapped deployment	Yes	No
LLM provider	Bring your own (GPT, Claude, Gemini, Llama, Mistral, local models)	Limited to OpenAI, Anthropic, Google within Glean’s platform
Vector database	Bring your own (Qdrant, Pinecone, Weaviate, etc.)	Proprietary, non-negotiable
Custom agents	Config-based with MCP tools, portable	No-code builder, locked to Glean’s platform
Data ownership	Customer owns all infrastructure and data	Data lives in Glean’s proprietary Enterprise Graph
Vendor lock-in	Low (open infrastructure)	High (proprietary indexes, non-portable agents, multi-year contracts)
Target scale	Teams of any size	500+ employee enterprises
Pricing transparency	Transparent	Opaque (requires sales engagement)
Vertical specialization	Property management automation, general enterprise	Horizontal only

Deployment: Where Does Your Data Live?

Glean

Glean is fundamentally a cloud-native platform. Their default deployment is hosted by Glean on their infrastructure. They offer a “customer-hosted cloud” option where the platform runs inside your AWS, Azure, or GCP account, but there is no true on-premises option.

This means:

No air-gapped deployments for regulated industries (defense, healthcare, financial services)
Your data always requires a cloud provider relationship
Compliance with data residency requirements depends on Glean’s regional availability (AMER, EMEA, APAC)

Agora

Agora offers three deployment models with full parity:

On-premises: Deploy with a single Helm command. Fully air-gapped. Nothing leaves your network.
Private cloud: Dedicated tenant on your cloud infrastructure with complete data isolation.
Managed cloud: Fully managed with auto-scaling for teams that don’t want to self-host.

For organizations in regulated industries (banking, government, defense, healthcare) the ability to run entirely on-premises with no external data dependencies is not optional. It’s a requirement.

LLM Flexibility: Who Controls the Brain?

Glean

Glean lets administrators select from a curated set of models (OpenAI GPT, Anthropic Claude, Google Gemini) within their platform. They route different tasks to different models: coding to Claude, creative work to Gemini, general reasoning to GPT.

However:

You cannot bring your own fine-tuned model
You cannot use open-source models (Llama, Mistral, DeepSeek)
You cannot self-host an LLM and connect it to Glean
You rely on Glean’s contractual agreements with model providers (zero-retention), not your own
Model availability depends on Glean’s roadmap, not yours

Agora

Agora is model-agnostic by design:

Any commercial provider: GPT, Claude, Gemini
Any open-source model: Llama 3, Mistral, DeepSeek, Phi, JAIS
Self-hosted models: Run inference on your own hardware
AWS Bedrock, Azure AI, GCP Vertex: Use your existing cloud AI agreements
Switch providers without migration: The retrieval layer is decoupled from the generation layer

This means you can start with OpenAI today, switch to a self-hosted Llama deployment tomorrow, and add Claude for specific use cases, all without changing your data pipeline or agent configurations.

Vector Database: Who Owns Your Search Index?

Glean

Glean uses a proprietary indexing system built on their “Enterprise Graph,” a knowledge graph encoding entities, relationships, and organizational context. This is powerful, but entirely non-portable.

You cannot export your indexed data
You cannot choose a different vector database
If you leave Glean, you lose years of accumulated organizational knowledge encoded in their graph
The index structure is opaque: you cannot inspect, modify, or extend it

Agora

Agora lets you bring your own vector database:

Qdrant (default): high-performance, open-source
Plug in Pinecone, Weaviate, Milvus, pgvector, or any compatible vector store
Your embeddings, your collections, your infrastructure
Full visibility into how documents are chunked, embedded, and indexed
If you leave Agora, your vector data stays with you

Your search index is an asset you own, not a dependency you rent.

AI Agents: Portable vs. Platform-Locked

Glean

Glean offers a no-code agent builder and agent orchestration. Agents can be triggered by events, route tasks between each other, and act autonomously. There’s a shared library of templates.

The limitation: these agents exist only within Glean. They cannot:

Run outside Glean’s infrastructure
Be exported to another platform
Operate independently of Glean’s Enterprise Graph
Use tools outside Glean’s ecosystem (without custom integration)

Agora

Agora treats agents as configuration:

agent:
  name: "Engineering Knowledge Assistant"
  model: gpt-4.1
  provider: openai
  system_prompt: "You are a technical assistant..."
  tools: [rag_search, fetch_property, web_search]
  max_iterations: 5
  triggers: [webhook, schedule]

Agents are:

Defined as config: version-controlled, auditable, reproducible
Tool-based via MCP (Model Context Protocol): connect any tool
Provider-flexible: same agent can run on different LLMs
Self-hosted or managed: run the orchestration loop yourself or use Anthropic Managed Agents
Portable: your agent definitions work regardless of where they run

Data Source Integrations

Glean

Glean has a clear advantage in breadth: 100+ pre-built connectors covering CRM (Salesforce, HubSpot), communication (Slack, Teams), engineering (GitHub, Jira), HR (Workday), and more. Their connector library is mature and well-maintained.

Agora

Agora currently supports the most critical knowledge sources:

Confluence, Notion, Google Drive: core documentation platforms
AWS S3, GCP Storage, Azure Storage: cloud file storage
WikiJS: open-source wiki platforms
File uploads: direct document ingestion (PDF, DOCX, HTML, Markdown, audio, video, images)
Custom connectors via API

For organizations whose critical knowledge lives in documentation platforms, cloud storage, and internal wikis (which covers the majority of enterprise knowledge management needs) Agora provides comprehensive coverage. Additional connectors are on the roadmap.

Document Processing

Glean

Glean ingests and indexes content from connected sources. Details of their processing pipeline are not publicly documented.

Agora

Agora’s document processing pipeline is transparent and handles:

PDF: Full extraction with OCR for scanned documents
Office documents: DOCX, XLSX, PPTX conversion
Images: Tesseract OCR + TrOCR for handwritten content
Audio: OpenAI Whisper transcription
Video: Frame extraction + audio transcription combined
Markdown/HTML: Direct indexing with structure preservation
Deduplication: Perceptual hashing to avoid redundant content

The pipeline: Extract -> Convert to Markdown -> Chunk -> Embed (OpenAI text-embedding-3-small, 1536-dim) -> Index in vector DB. Every step is visible and configurable.

Security and Permissions

Glean

Single-tenant isolated deployments
Real-time permission enforcement from source systems
Zero-retention agreements with LLM providers
Sensitive data detection and remediation
Agent governance controls
SOC 2 compliance

Agora

Per-request audit trail (BigQuery logging)
RBAC at document, source, and agent level
SSO via Firebase (OIDC/SAML capable)
Encryption at rest and in transit
Org-scoped data isolation (multi-tenancy)
Feature toggle system for granular access control
On-premises option: when your security requirement is “data never leaves the building,” only on-prem satisfies it

The key difference: Glean’s security depends on trusting Glean’s infrastructure and their third-party agreements. Agora’s on-premises deployment means security is entirely under your control.

Pricing and Total Cost of Ownership

Glean

Glean does not publish pricing. Based on publicly available contract data:

Median contract: ~$98,100/year
Range: $28,500 to $202,000+/year
Structure: Per-user licensing, multi-year commitments (2-3 years for best rates)
Hidden costs: Implementation fees, custom integrations, training, 3-7% annual price escalations
Minimum: Likely 100+ user minimum
No self-serve option: requires sales engagement

Agora

Agora offers transparent, predictable pricing designed for teams of any size. No surprise escalation clauses, no multi-year lock-in requirements. Contact us for details tailored to your deployment model and scale.

Vendor Lock-In: The Long Game

This is perhaps the most important consideration for any enterprise infrastructure decision. AI search is not a tool you swap out easily. It becomes the knowledge layer your entire organization depends on.

Glean’s Lock-In Vectors

Enterprise Graph: Your organizational knowledge, relationships, and context accumulate in Glean’s proprietary system. This is non-portable.
Proprietary indexes: All your document embeddings and search indexes live in Glean’s infrastructure. No export.
Agent ecosystem: Custom agents built in Glean cannot run elsewhere.
Enterprise Memory: Behavioral patterns and workflow traces stored in Glean’s system.
Multi-year contracts: 2-3 year commitments standard, with annual price escalations.
Switching cost: Leaving means rebuilding your knowledge layer from scratch.

Agora’s Approach

You own the vector database: your embeddings are yours
You own the infrastructure: on-prem or your cloud account
Agent configs are portable: JSON/YAML definitions, not platform-locked
No multi-year lock-in: month-to-month available
Standard formats: Markdown chunks, OpenAI-compatible embeddings, standard APIs

When to Choose Glean

Glean is the right choice when:

You’re a 500+ employee enterprise with budget for $100K+/year
You need 100+ pre-built connectors immediately
Your security requirements allow cloud-hosted solutions
You want a fully managed, zero-infrastructure-management experience
Your team prefers no-code agent building over configuration-as-code
You’re comfortable with long-term vendor commitment

When to Choose Agora

Agora is the right choice when:

You need on-premises or air-gapped deployment (regulated industries, defense, healthcare, finance)
You want to bring your own LLM, including open-source or self-hosted models
You need data sovereignty: your indexes, your infrastructure, your control
You want to avoid vendor lock-in: portable agents, standard embeddings, no proprietary graph dependency
You need custom agent workflows with MCP tool integration
You’re building AI infrastructure that you want to own long-term
You operate in the property management / short-term rental vertical and need booking platform automation
You need a solution that works at any scale, from a 10-person team to thousands

The Bottom Line

Glean is a polished, enterprise-grade product with impressive breadth. For large organizations that are comfortable with cloud-only deployment and long-term vendor commitment, it delivers a comprehensive solution.

Agora is built for organizations that believe their AI knowledge infrastructure should be an asset they own, not a service they rent. If you need deployment flexibility, model freedom, data sovereignty, and freedom from lock-in, Agora gives you that without sacrificing capability.

The question is not just “which platform has better search today?” It’s “who controls our knowledge infrastructure in five years?”

Ready to see Agora in action? Book a demo or try the console to explore what’s possible when you own your AI infrastructure.