Multi-Agent Interoperability

Every agent.
One governed layer.

Your enterprise won't run on one vendor's agents. It will run on dozens. Tantor's multi-agent interoperability layer ensures they all communicate, collaborate, and comply — regardless of platform.

Any framework
Agent origin
100%
Cross-agent interactions governed
0
Context lost at boundaries
Single
Governance layer for all

From source
to governed output.

1

Connect

Register agents from any platform — Tantor-native, third-party, or custom-built

2

Standardise

Normalise context formats, memory models, and tool-calling conventions across frameworks

3

Govern

Apply access policies, PII masking, and audit logging to every cross-agent interaction

4

Communicate

Agents exchange context, intermediate results, and governance metadata — cleanly

5

Audit

Every cross-agent interaction logged — who said what, what data was shared, what policy applied

Three problems.
One root cause.

Without a governed platform, these problems compound with every new data source and every new AI deployment.

The many-frameworks problem.

Enterprise AI agents are built on different platforms. Each has its own context format and tool-calling conventions. Connecting them requires custom integration for every agent pair.

Context lost at boundaries.

When Agent A completes a task and Agent B picks up, context rarely transfers cleanly. Intermediate conclusions, confidence scores, and governance metadata are lost.

Governance ends at the platform edge.

Your platform governs its native agents. But the moment an agent communicates with an external agent, the governance trail breaks — creating the same compliance risk as an ungoverned data export.

What multi-agent interoperability
delivers.

🌐

Universal agent connectivity.

Connect agents from any framework — LangChain, CrewAI, AutoGen, vendor-native, or custom-built — through a standardised interoperability layer.

📦

Context preservation across boundaries.

Intermediate conclusions, confidence scores, governance metadata, and decision rationale transfer cleanly between agents — no reconstruction from scratch.

⚖️

Governance that follows the interaction.

Access policies, PII masking, and audit logging apply to every cross-agent communication — regardless of which platform initiated it.

📋

Full interaction audit trail.

Every cross-agent interaction logged — which agent, what data was exchanged, what policy applied, what the outcome was.

Built with
regulators in mind.

📋

Interaction Audit

Every cross-agent communication logged with agent identity, data exchanged, and policy applied.

🔐

PII at Every Boundary

Masking policies enforced on every agent-to-agent data exchange — not just at human interfaces.

Context Lineage

Governance metadata and decision rationale preserved across every agent boundary.

⚖️

Policy Enforcement

Access controls applied to cross-agent interactions as rigorously as to direct data queries.

All your agents.
One governance layer.

See how Tantor's multi-agent interoperability layer connects agents from any platform under a single, governed communication standard — with full audit trails across every interaction.