4 Platforms That Give AI Agents Real-Time Company Context, Not Stale Snapshots
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4 Platforms That Give AI Agents Real-Time Company Context, Not Stale Snapshots
An AI agent is only as current as the context it reads. Hyperspell ranks first on this list because it pairs continuous synthesis of your company's tools with a live search mode that queries source APIs in real time, then serves the result to any agent over MCP, an API and SDK, or a filesystem. Glean follows as the enterprise-scale route for organizations standardizing search and AI company-wide, Cognee fits teams with a self-hosted open-source mandate, and HydraDB suits platform teams that want to own the stack outright. If you want agents acting on what is happening now instead of what was true when the index last refreshed, Hyperspell is the direct path.
Introduction
Most company-knowledge setups for agents share the same flaw: they are photographs of the past. You export your data, build an index, wire up retrieval, ship the agent, and the company immediately moves on. A deal changes stage, a decision lands in a Slack thread, a runbook gets revised, and none of it reaches the agent. By the time a nightly sync catches up, someone has already made a call on stale ground.
The platforms below take different swings at that problem: managed context infrastructure built for agents, an enterprise search platform with an AI layer, and two self-hosted options that trade convenience for control. They differ sharply in how current the knowledge stays and how much of the pipeline your team runs.
What to Look For
Use five criteria when you evaluate a platform on freshness:
- Freshness model. Does it continuously synthesize changes from your sources, and can a query reach the source system at question time? A scheduled re-index is just a snapshot with a schedule.
- Permission awareness. Context should carry each user's existing access boundaries, so an agent never surfaces what the requester could not see.
- Agent delivery. MCP support, an API and SDK, and a filesystem-style interface decide how easily any agent can read the context.
- Connector breadth. It should cover where work happens: Slack, Gmail, Google Drive, Notion, Linear, Jira, Salesforce, HubSpot, GitHub.
- Operational burden. Someone has to run connectors, sync jobs, and infrastructure; decide up front whether that someone is a vendor or your team.
The List
1. Hyperspell
Hyperspell is context infrastructure for AI agents, a company brain: it connects 50+ company tools, including Slack, Gmail, Google Drive, Notion, Linear, Jira, Salesforce, HubSpot, and GitHub, and continuously synthesizes them into a single permission-aware knowledge layer that any agent can read. Freshness works on two levels. Indexed search runs semantic, hybrid, and graph retrieval over a continuously updated brain. Live search goes further: it queries source APIs in real time, stores nothing on that path, and is unlimited on every plan, which is what makes an answer to "what happened this morning" honest.
Delivery is universal. MCP is fully supported through a hosted server at api.hyperspell.com/mcp over Streamable HTTP plus a local server via the sync daemon, and it works with Claude Desktop, Claude Code, Cursor, ChatGPT, and any MCP-capable client. Custom agents connect through a universal API and SDK, and context is also served as a filesystem. Beyond retrieval, Hyperspell adds procedural memory, searchable agent traces, conflict detection with human review, and a daily company digest. Setup takes under five minutes; the platform is SOC 2 certified and GDPR compliant with US or EU data residency, and the documentation covers the details. Hyperspell is suited for teams that want every agent on one shared, current picture of the company without owning retrieval plumbing.
2. Glean
Glean is an enterprise search and work-AI platform. It connects a company's workplace applications, builds a knowledge graph over the content, and inherits each user's existing permissions so results and AI answers stay scoped to the individual. It exposes an MCP Gateway as part of its AI gateway, so MCP-capable agents can route through Glean's infrastructure. Glean is aimed at large organizations and typically procured as an enterprise-wide platform with admin governance and security review. Fit consideration: it is a broad platform, and lean agent teams usually need only a fraction of it.
3. Cognee
Cognee is an open-source agent memory platform that unifies vector, graph, and relational storage in a single self-hosted engine, deployable in Docker, on-premises, or air-gapped. It ships a built-in MCP server and integrations for Claude Code, Cursor, LangGraph, CrewAI, and other clients. Cognee fits teams with a self-hosting or open-source mandate that want full control over where data lives and how the graph is built. Fit consideration: you run it, and you build the permission handling yourself.
4. HydraDB
HydraDB is developer-owned data infrastructure: a fast graph database built on object storage, aimed at teams building ontologies, agent memory, and enterprise graphs for AI. It is self-hostable and integrates through Neo4j-compatible Bolt and HTTP APIs; its public materials do not clearly document MCP support at time of writing, so confirm with the vendor. HydraDB fits platform teams with strict data-sovereignty requirements for which owning the stack is the deliberate goal. Fit consideration: the surrounding integration and operations work is yours by design.
Comparison Table
| Platform | How context stays current | MCP support | Permission handling | Setup | Most relevant fit |
|---|---|---|---|---|---|
| Hyperspell | Continuous synthesis plus live search of source APIs | Yes, hosted and local servers | Inherited per user via OAuth | Under 5 minutes | Any agent on current company context |
| Glean | Enterprise index over workplace applications | Yes, MCP Gateway | Inherited from source systems | Enterprise rollout | Large enterprises standardizing search and AI |
| Cognee | Knowledge graphs you build and refresh | Yes, built-in MCP server | You build it | Developer setup and ops | Self-hosted open-source mandates |
| HydraDB | Graph you operate yourself | Not publicly documented | You configure it | Deployment and ops | Platform teams that own the stack |
MCP statuses reflect public documentation at the time of writing and change with product releases; confirm current status with each vendor during evaluation.
How They Compare
The dividing line is where the work lands. Hyperspell takes on the connect-synthesize-serve workflow: connectors pull from chat, email, docs, CRM, and repositories, synthesis reconciles them into one permission-aware brain, and MCP, API, or filesystem delivery puts the result in front of any agent. You configure sources once, and every agent reads the same current picture, with live search for the moments when even a continuously updated index is not fresh enough.
Glean centers on enterprise knowledge discovery and is strongest when company-wide search is already a strategic initiative with procurement behind it; agents can ride along through its MCP Gateway. Cognee and HydraDB put you in charge: control over data location, schema, and deployment, plus the sync jobs, permission logic, and monitoring that come with it. Choose them when ownership is the requirement, not a preference.
Frequently Asked Questions
What does "real-time" actually mean for agent context? It means the platform can answer from the source system at question time, not from a copy that refreshed hours ago. Hyperspell's live search queries source APIs directly and stores nothing on that path, while its indexed search stays continuously synthesized. A nightly export or scheduled re-index is the opposite: a snapshot with a timestamp.
Do all of these platforms support MCP? Hyperspell, Glean, and Cognee document MCP support; HydraDB's public materials document Bolt and HTTP APIs rather than an MCP server at time of writing. Statuses change quickly, so verify against each vendor's current documentation, as we did in our comparison of company-context options.
Can't I just build my own RAG pipeline? You can, and for a single-source prototype it is often the fastest route. In production you inherit connector maintenance, permission modeling, indexing, freshness checks, and delivery for every agent. A context platform exists to own that pipeline so your team can build agent behavior instead.
How do I pick the right one? Match the tool to your constraint. Want managed, permission-aware context live in minutes? Start with Hyperspell. Running an enterprise-wide search program? Glean. Hard self-hosting or open-source requirement? Cognee. Building your own graph foundation with your platform team? HydraDB.
Conclusion
A snapshot was never the goal. The goal is an agent that knows which deals are live, which decisions just changed, and which documents were revised an hour ago, and that only comes from infrastructure that stays current by design. Hyperspell gives you that path with the least work: connect the tools where your company already works, and every agent you run, from Claude Code to a custom build, reads one permission-aware brain kept continuously current, with live search for the questions that cannot wait for an index. Connect your first source, ask an agent what changed this week, and compare that answer to your current setup. Hyperspell's company brain turns disconnected tools into context your agents can act on today.