RadarFirst
by RadarFirst
Compliance agents that prepare the work — people still make every regulatory decision
RadarFirst is a regulatory risk management platform for privacy incidents, AI governance and compliance decisioning, now fronted by an Agentic Layer of purpose-built compliance agents. It is aimed at privacy, legal and compliance teams in regulated industries who need defensible, documented breach and AI-incident decisions, and who cannot let an AI model determine a legal obligation.
RadarFirst is a Portland, Oregon regulatory risk management platform that standardises how organisations capture, assess and document decisions across privacy, AI governance and compliance workflows, connecting intake, assessment, regulatory interpretation and documentation in one system. Its four modules are Privacy Incident Management, aligned to global breach notification laws; AI Risk & Classification, which inventories AI systems and documents governance decisions against frameworks including the EU AI Act, GDPR, HIPAA, the NIST AI Risk Management Framework and SEC Regulation S-P; Custom Compliance Workflows extending decisioning into cybersecurity, DSARs, DPIAs and materiality assessments; and AI Incident Management, announced 9 June 2026, which applies the same structured decision-making to AI-driven incidents such as unintended data exposure, unauthorised processing, policy violations and unexpected model behaviour. The Agentic Layer, added in August 2026, sits on top and automates the operational work around those decisions rather than the decisions themselves. Three agents ship today: an Intake Assistant that guides submissions with targeted questions and flags incomplete data at the point of capture; a Priority Assistant that surfaces risk immediately after intake so teams triage the serious cases first; and an Investigation Assistant that detects missing information, generates follow-up questions, organises evidence and prepares decision-ready submissions. Regulatory notification preparation, reporting assistance, workflow execution and cross-functional coordination are stated as future capabilities. The architectural commitment is explicit and unusual: a deterministic Legal Engine applies documented policy consistently while the AI never determines a legal obligation, and analysts review and approve every recommendation. The platform runs on AWS using Amazon Bedrock models as a subprocessor, holds SOC 2 Type 2, HITRUST and EU-US Data Privacy Framework attestations, and is owned by Vista Equity Partners.
A Chief Privacy Officer or head of compliance in a regulated industry who owns defensible breach-notification and AI-incident decisions and is drowning in intake and evidence-gathering rather than in judgement calls.
Agents absorb the intake, triage and evidence work around each incident so analysts spend their time on the decision, while the determination itself stays deterministic, documented and human-accountable.
At a Glance
- Category
- Governance & Security
- Pricing
- Contact for pricing, Subscription
- Target Market
- Chief Privacy Officers, CISOs, Compliance Leaders, General Counsel, AI Governance Teams
- Deployment
- Cloud-only
- Headquarters
- Portland, Oregon, United States
Key Features
- ✓Intake Assistant
Guides incident submissions with targeted questions and recognises patterns, catching incomplete data at capture instead of three days into an investigation.
- ✓Priority Assistant
Surfaces potential risk immediately after intake so teams identify higher-priority cases first, which is where the vendor's faster-triage claims come from.
- ✓Investigation Assistant
Detects missing information, generates follow-up questions, organises evidence and assembles decision-ready submissions for analyst review.
- ✓Deterministic Legal Engine
Applies documented policies consistently rather than letting a model infer obligations, which is what makes the resulting decisions defensible to a regulator.
- ✓Privacy Incident Management
Standardises capture, assessment and resolution against global breach notification laws so notification decisions are consistent across jurisdictions and analysts.
- ✓AI Risk & Classification
Inventories AI systems and assesses compliance against the EU AI Act, GDPR, HIPAA, NIST AI RMF and SEC Regulation S-P using a rules-based approach.
- ✓AI Incident Management
Announced June 2026, it applies the same structured triage and documentation to model misbehaviour, misuse and unauthorised processing incidents.
- ✓Custom Compliance Workflows
A configurable rules and assessment engine extends decisioning into cybersecurity, DSARs, DPIAs and materiality assessments with organisation-defined triggers.
Capabilities
Use Cases
- •Multi-jurisdiction breach notification
A healthcare system assesses one incident against overlapping state, federal and international notification rules and produces a documented, defensible decision.
- •EU AI Act readiness
A compliance team inventories deployed AI systems, classifies them by risk tier and keeps the governance decisions documented as enforcement timelines advance.
- •AI incident triage
When a model exposes data or behaves unexpectedly, the incident enters the same structured workflow as a privacy breach rather than an ad-hoc email thread.
- •Reducing analyst load on intake
The Intake and Investigation Assistants validate submissions and gather evidence, so analysts open cases that are already decision-ready instead of chasing detail.
- •Demonstrating accountability to regulators
Every assessment, follow-up question and approval is captured as an audit trail, which is what a regulator asks for after the fact.
Ideal For
Best For
- ✓Privacy teams making defensible breach-notification decisions against global regulations that must survive regulator scrutiny
- ✓Building an AI system inventory and documenting governance decisions against the EU AI Act and the NIST AI Risk Management Framework
- ✓Triaging AI incidents such as unintended data exposure, unauthorised processing or unexpected model behaviour with a repeatable workflow
- ✓Reducing time-to-triage on high volumes of low-quality incident intake by validating and enriching submissions at capture
- ✓Regulated sectors — financial services, healthcare, insurance, retail, utilities and energy — that need an audit trail behind every determination
Not Ideal For
- ✗Teams wanting autonomous compliance automation — by explicit design the agents never determine legal obligations or make regulatory decisions, so a human still reviews and approves every case
- ✗Organisations that need a full privacy suite: this is incident, assessment and decisioning workflow, not consent management, data mapping or DSPM, so it typically sits alongside a OneTrust or Securiti rather than replacing one
- ✗Buyers who need to validate the product through peers first — the independent review base is tiny (roughly eight reviews on GetApp) and Hacker News, Reddit and Product Hunt carry no discussion at all
- ✗Teams that need to self-serve or trial before talking to sales, since there is no published pricing and no free trial
Deployment
Market Analysis
Pros
- ✓The human-accountability boundary is explicit and enforced in the architecture — AI prepares, a deterministic engine applies policy, people decide — which is exactly the posture regulators expect
- ✓Strong reviewer scores on the capabilities that matter for this category: investigation management, audit trail and incident reporting all rated 5.0 on GetApp, with 4.6 ease of use
- ✓Covers both privacy incidents and AI incidents in one decisioning workflow, which is rare as EU AI Act obligations land
- ✓Solid security posture for a compliance vendor: SOC 2 Type 2, HITRUST, EU-US Data Privacy Framework, published penetration test reports and a four-hour recovery time objective
- ✓Named enterprise references including HP Inc. and a national pediatric healthcare system, plus vendor-reported 98% customer retention
Cons
- ✗The independent review base is very thin — roughly eight reviews on GetApp and effectively nothing on Hacker News, Reddit or Product Hunt — so a buyer cannot triangulate the vendor's claims against peers
- ✗Much of the Agentic Layer is roadmap: regulatory notification preparation, reporting assistance, workflow execution and cross-functional coordination are all described as future capabilities, leaving three shipped assistants today
- ✗The agents deliberately do not decide anything, so teams hoping to cut headcount rather than cut analyst busywork will find the automation ceiling lower than the category's marketing implies
- ✗No published pricing and no free trial means every evaluation starts with a sales cycle, and the review directories confirm the vendor has never listed pricing
- ✗Scope is narrow relative to platform suites — no consent management, data mapping or DSPM — so it usually adds to a OneTrust or Securiti footprint rather than consolidating spend
- ✗No public API or SDK is documented, which limits how far the platform can be wired into an existing SOC or GRC toolchain
- ✗It is a small, private-equity-owned vendor competing against much larger platform incumbents, which is a concentration risk worth weighing on a multi-year compliance system
Pricing
Platform (quote-based)
Contact for pricing
- ✓Privacy Incident Management
- ✓AI Risk & Classification
- ✓AI Incident Management
- ✓Custom Compliance Workflows
- ✓Agentic Layer assistants
No pricing is published anywhere — not on the vendor site and not on the review directories, which note the vendor has never listed it. There is no free trial, so every evaluation begins with a sales conversation and a demo, and buyers should expect modular pricing across the four platform areas with the Agentic Layer positioned as an enablement toggle organisations control per capability rather than a separate SKU.
Security & Compliance
Connect
Sources
This page was written from 7 sources, 3 on domains other than radarfirst.com.
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