Complyance, an AI-native governance, risk, and compliance startup, has secured a $20 million Series A led by GV to bring continuous, automated oversight to enterprise risk programs. The company, which emerged from stealth in 2023 and began selling late in 2024, says the funding will accelerate go-to-market efforts and expand its library of specialized AI agents built to handle the grunt work that bogs down GRC teams.
AI-Native Approach To Continuous Compliance
At its core, Complyance plugs into a company’s existing tech stack and deploys AI agents that continuously test controls, assess data handling against policy, and flag exceptions for human review. Instead of waiting for quarterly or annual audits, the platform runs bespoke checks in near real time, shrinking review cycles from weeks to minutes and reducing the chance that gaps linger unnoticed.
This “always-on” posture matters as control frameworks and regulatory expectations multiply. Enterprises now juggle SOC 2 evidence collection, ISO 27001 control mapping, PCI DSS 4.0 updates, HIPAA safeguards, and fast-evolving data residency rules. Complyance’s agents are designed to automate evidence gathering across systems, map findings to relevant frameworks, and route only material issues to analysts—freeing teams from manual screenshots and spreadsheet wrangling.
The platform also targets third-party and fourth-party risk, a chronic weak spot. As companies rely on cloud providers, data brokers, and AI services, vendor assessments can become a bottleneck. Complyance uses agents to ingest vendor documentation, evaluate control strength against internal thresholds, and trigger deeper reviews when signals look off. The approach mirrors what security leaders increasingly demand: less questionnaire theater, more continuous assurance.
The stakes are high. IBM’s Cost of a Data Breach Report found the global average breach cost rose to $4.88 million in 2024, and the Verizon Data Breach Investigations Report has repeatedly flagged third-party exposure as an outsized contributor to incidents. Continuous control monitoring and automated evidence capture have shifted from “nice to have” to board-level priorities as a result.
A Crowded Field And A Clear Differentiator
Complyance enters a mature arena with established platforms like Archer, ServiceNow GRC, and OneTrust. Where the startup draws a bright line is by being built AI-first rather than layering machine learning on top of legacy workflows. That architecture makes it easier to introduce specialized agents that perform narrow tasks end to end—think automated access review sampling or data classification validation—while maintaining auditability and human oversight.
Analysts at Gartner and Forrester have tracked growing demand for integrated risk management platforms that emphasize automation and outcome-based reporting. The shift is driven by two realities: compliance is increasingly continuous, and risk leaders need time back for strategy, not checkbox chores. Complyance is betting that AI-native workflows—complete with explainable findings and control lineage—will win over teams under pressure to do more with less.
Funding Details And Product Roadmap For Complyance
The round was led by GV, with participation from Speedinvest, Everywhere Ventures, and angel investors affiliated with Anthropic and Mastercard. Including this financing, Complyance has raised $28 million to date. While the company has not disclosed customer counts, it says it is already embedded with several Fortune 500 organizations—an early signal that the product can navigate enterprise procurement and security reviews.
The new capital will support go-to-market expansion and R&D. Complyance currently fields 16 purpose-built agents and plans to release roughly 30 more, targeting high-friction workflows such as continuous vendor monitoring, automated control testing across cloud environments, and policy-to-technical-control translation. The ambition is to hand GRC leaders a set of autonomous helpers that keep controls effective between audits, not just documented at audit time.
Why Timing Favors Continuous GRC Across Enterprises
Regulatory momentum is pushing risk programs toward real-time visibility. In the US, new cybersecurity disclosure rules have heightened board scrutiny of material incidents and risk governance. In Europe, the Digital Operational Resilience Act and NIS2 are widening operational and third-party obligations. Meanwhile, the EU AI Act and emerging model risk guidance are prodding companies to track how data is used inside and alongside AI systems.
Against that backdrop, the winning playbook blends automation with accountability. Tools must collect durable evidence, preserve an audit trail, and make it easy to prove that controls work as designed. But they also need to let humans steer: exceptions, risk appetite decisions, and compensating controls remain judgment calls. Complyance’s pitch aligns with that reality—use AI to clear the noise, elevate the signal, and give scarce experts time to focus on the risks that move the needle.
If the company can continue converting large enterprises and demonstrate measurable reductions in audit prep time, issue closure cycles, and vendor review backlog, it will have a compelling case in a market that rewards results. With fresh funding, an AI-first architecture, and a swelling regulatory tide, Complyance is well positioned to test whether autonomous GRC agents can finally deliver on the promise of continuous compliance.
