AvePoint Trust Platform targets the agentic AI governance gap
AvePoint, the Nasdaq- and SGX-listed data-management company, has launched its Trust Platform, a product designed to give enterprises continuous visibility and policy enforcement over the AI agents, models, and tools operating inside their organisations. The launch marks a strategic pivot from AvePoint's legacy of Microsoft 365 data management into the fast-emerging discipline of AI governance, a market being shaped by the rapid proliferation of agentic AI systems across cloud environments.
The catalyst is well-documented: as organisations delegate more operational tasks to AI agents, those systems gain broad and often poorly-audited access to sensitive data. AvePoint's own State of AI 2026 Report found that 88.4% of organisations experienced at least one AI agent-related security incident in the past twelve months, a figure the company says held even among those confident in their access controls. The problem, in AvePoint's framing, is not malicious intrusion but authorised overreach: an agent reads everything it is permitted to read and can act on it thousands of times an hour without triggering a single rule.
From data protection to AI trust
The Trust Platform is structured around four disciplines: Observe, which maps what agents can reach and flags overshared or unlabelled content before an agent encounters it; Protect, which extends backup and recovery to agents themselves, including their configuration logic and prompt flows; Govern, which assigns each agent an owner, a policy, and a data-sensitivity context; and Optimise, which surfaces token consumption and AI spend data to help finance and IT teams evaluate return on investment. The platform operates across major cloud and AI providers, covering Microsoft Copilot Studio and Foundry, Google Vertex AI, Salesforce Agentforce, and now Anthropic Claude, along with MCP server discovery.
A Governance Graph underpins the platform, connecting global regulatory frameworks including the EU AI Act, ISO 42001 and the NIST AI Risk Management Framework to each organisation's internal context: its data owners, information barriers, and the stated purpose of every workspace and agent.
"Every organisation now has access to the same AI capabilities," said Dr Tianyi Jiang, CEO and Co-Founder of AvePoint. "What truly sets them apart is how far that AI can safely reach, what permissions it actually has, and whether there's a way to reverse course when it makes a wrong call."
EY's AI Workplace Practice is named as a launch partner, with Sr. Managing Director Randy Simmons citing the platform as addressing a "critical need" in the large enterprise market.
The broader governance market shaping up
The AvePoint launch sits inside a rapidly consolidating market for AI governance tooling. Gartner projects worldwide AI spending will grow 49.5% in 2026, a rate that is outpacing most enterprises' ability to audit what that spend is actually doing inside their systems. That gap is attracting a new category of vendors positioned between the hyperscaler security suites (Microsoft Purview, Google Cloud's security offerings) and specialist compliance platforms.
For cross-sector strategists, the significance extends beyond cybersecurity. AI governance is becoming a compliance prerequisite in regulated industries: financial services firms face obligations under the EU AI Act and incoming UK AI governance codes; pharmaceutical and biotech organisations using AI in drug development face FDA and EMA scrutiny over model provenance and audit trails. A platform that can produce signed, audit-ready evidence of agent behaviour across cloud vendors is increasingly a procurement requirement, not an optional upgrade. Capital is beginning to follow: AI governance and observability startups attracted notable venture interest through 2025 and 2026, and larger data-management incumbents like AvePoint are repositioning to defend their enterprise relationships as the agentic layer consolidates above the cloud infrastructure layer.