Data Provider for AI Agents
Data Sharing Infrastructure for Autonomous AI Agents
AI agents operate autonomously—requesting data, making decisions, and taking actions without human intervention. This creates unique data sharing challenges: How do you verify an agent's identity? How do you manage consent for autonomous access? How do you prevent scope creep? Fiskil Data Provider answers these questions with agent-native infrastructure.
The Challenge
Traditional data sharing was designed for human users clicking through consent screens. AI agents can't authenticate through browser redirects, don't have human judgment about data access, and operate at machine speed. Without agent-specific infrastructure, enterprises either block agent access entirely or create dangerous security gaps.
The Solution
Fiskil Data Provider introduces agent-native data sharing: machine-to-machine authentication, programmatic consent flows, agent identity verification, and real-time access monitoring. Agents register through an API, receive scoped credentials, and access data within strictly defined boundaries—all logged and auditable.
Benefits
Key Benefits
Agent Identity Verification
Register and verify AI agent identities with cryptographic credentials. Each agent gets a unique identity tied to its operator, purpose, and access tier.
Programmatic Consent
Machine-readable consent flows designed for autonomous systems. Agents request access programmatically and receive scoped tokens without human-in-the-loop bottlenecks.
Real-Time Access Controls
Dynamic access policies that adapt in real-time. Rate limiting, scope enforcement, and anomaly detection prevent agents from exceeding their authorized boundaries.
MCP Protocol Support
Native support for Model Context Protocol and other agent communication standards. Agents connect using protocols they already understand.
Use Cases
Common Use Cases
Agentic Data Retrieval
AI agents autonomously query enterprise data sources to complete tasks. Agent registry ensures only verified agents access data, while consent scoping limits what each agent can retrieve.
Multi-Agent Orchestration
Complex workflows where multiple agents collaborate require coordinated data access. Fiskil manages token delegation between agents while maintaining audit trails for each access.
Agent-to-Agent Data Sharing
When agents need to share data between themselves, Fiskil provides secure relay infrastructure with consent enforcement at each handoff point.
Guides
Deep-Dive Guides
AI Agents
Agent Registry
Register, verify, and manage AI agents accessing your enterprise data. Fiskil's Agent Registry provides identity verification, risk scoring, certification tracking, and access tier management for the agentic AI economy.
AI Agents
Consent Management
Granular consent management designed for autonomous AI agents. Field-level access controls, purpose limitation, time-bounded permissions, and automated revocation for machine-to-machine data sharing.
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FAQs
Agents use machine-to-machine OAuth 2.0 flows with client credentials. Each agent receives cryptographic credentials tied to its registered identity, operator, and approved access scopes.
The Agent Registry is a managed directory of verified AI agents authorized to access your data. Each entry includes agent identity, operator details, risk tier, approved scopes, and access history.
Data owners define consent policies programmatically: which agents can access what data, for which purposes, and for how long. Agents receive scoped tokens that enforce these policies automatically.
Yes, agent access can be revoked instantly through the API or dashboard. Revocation propagates immediately, and the agent's tokens become invalid for all subsequent requests.
Yes, Fiskil Data Provider supports MCP as a native transport for agent data access, alongside REST APIs and GraphQL endpoints. Agents can connect using whichever protocol suits their architecture.
Strict scope enforcement at the API layer prevents agents from accessing data outside their approved boundaries. Anomaly detection flags unusual access patterns, and automated policies can restrict or revoke access if boundaries are tested.
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