Most AI reads a document. Aproove's AI reads every component inside it.
Atomic file breakdown gives our AI Agents a structured understanding of every file, down to the paragraph, image, and pixel. From that foundation, Agents scan a file, or specific parts of it, for compliance risk, brand risk, and regulatory exposure. They flag what they find, suggest what to fix, and route the work to the humans best equipped to decide.
It puts human decision makers where they need to be inside the AI-powered compliance platform.
What it is
AI-Powered Risk Detection is Aproove's framework for surfacing risk in your assets before, during, or after human review. Our AI Agents work inside the structured file representation produced at upload, which means they understand the file the way your reviewers do: as text, images, color, layout, brand elements, and metadata, not as a flat blob.
You can invoke an Agent manually from inside the Review Interface, or you can build an Agent into your workflow as an automatic action. Either way, Agents respect Aproove's permission model: who can see which Agent, who can invoke which Agent, and what files an Agent can access are all governed by user, role, or team.
When an Agent runs, it returns its findings as structured Tags and Notes placed against specific components of the file. Reviewers see exactly which paragraph, which image, or which page carries risk, what the Agent thinks the issue is, and what it suggests to address it. Humans confirm, override, or escalate. The audit trail captures every decision.
Why it matters
Compliance review at scale runs into the same tension every time, even with robust creative approval software involved. The volume of content keeps growing. The pool of qualified reviewers does not. Brand teams, legal teams, and regulatory specialists are expensive, in demand, and outnumbered by the assets they have to clear.
The traditional response is to stretch reviewers thinner: less time per file, or fewer reviewers per file, or both. The predictable result is compliance teams as bottlenecks and quality risk as a steady undercurrent.
An AI-powered compliance platform opens up new options. In Aproove, AI-Powered Risk Detection inverts the pattern. Agents do the first pass at the component level, surfacing what looks risky and routing those components, or those files, to the right humans. Reviewers no longer enter blind. They open a file already briefed on what the Agent found, with risk pre-tagged at the exact components that warrant attention, with suggested resolutions to consider. They enter with deep context, make better-briefed decisions, and focus on the components that actually need human judgment. Routine material gets cleared. Subject matter experts get protected for the work that needs them.
The Agent does not replace the reviewer. It changes what the reviewer is asked to do.
How it works in practice
- Atomic file breakdown happens at upload. Every component of the file (text, metadata, images, layout, color, brand elements) is extracted and indexed. This is the foundation everything else runs on.
- Agents are invoked. A reviewer can manually call an Agent from inside the Review Interface, if their role grants them access. Or the workflow can call an Agent automatically as a defined Action: pre-screening, mid-cycle check, final review. Different Agents are configured for different specialties: brand review, legal review, regulatory check, compliance scan, whatever your team has built.
- The Agent analyzes. It can scan the entire file or a specific component a reviewer points it at. It uses the structured representation, not a screenshot, so it sees the same components your humans do.
- Findings are written back to the file. Risk is flagged with structured Tags (severity, category) and Notes (specific issue, suggested resolution) placed on the exact paragraph, image, or region the Agent flagged. Reviewers see what the Agent saw.
- Workflow follows the risk. Pages or components flagged at high severity can route to subject matter experts. Lower-risk content can move to broader review. Or a human inherits the full file with the Agent's analysis already in hand, ready to filter.
- Humans decide. Every Agent finding sits in front of a human who confirms, overrides, or escalates. Decisions land in the audit trail.
Choose your AI
Most AI features in B2B software lock you into a single model from a single vendor. They offer a flat creative approval software at best. Aproove takes a different position. The platform's AI invocation layer is abstracted from the underlying model, which means you can choose the AI provider that fits each use case. Each Agent is designated to a specific LLM, so you can run a mix of models across your Agent library.
That includes:
- The frontier model of your choice. OpenAI today, with the architecture designed to expand as the AI ecosystem evolves. Pick the model with the strongest performance for your task.
- A mixture of models across Agents. A specialist legal Agent on one model. A brand Agent on another. A regulatory Agent on a third. Each tuned to what it does best.
- Your own enterprise LLM. If your organization has standardized on an internal model, your Agents can run against it. Bring your own API keys, your own governance, your own usage policies.
- An Aproove-tuned custom LLM. Where general-purpose models are not enough, our Professional Services team can fine-tune a model against your content, your style guide, and your compliance requirements.
AI quality varies by task, by domain, and by content type. Forcing every Agent through one model is forcing every reviewer to wear the same prescription glasses. Aproove lets you match the model to the work.
Built with you: professional services
Trust in AI-driven review is earned, not assumed. Our Professional Services team works alongside your compliance, brand, and legal stakeholders to design Agents that meet your standards. That includes:
- Defining the review tasks an Agent should perform, and the ones it should not.
- Tuning prompts and reference material so the Agent reflects your style guide, your brand rules, your regulatory framework.
- Setting quality bars and validation tests before an Agent goes live in production.
- Iterating on Agent performance as your content evolves and your team gives feedback.
The result is Agents your teams trust because they were built with your teams.
Benefits
- Reviewers enter with context. Humans open files already briefed on what the Agent found and where, instead of starting from page one.
- Subject matter experts get protected. The high-cost reviewers in your organization see only the components that need their judgment, not every page of every file.
- Risk surfaces earlier. Pre-screening with an Agent at ingestion catches issues before they enter the human review queue.
- Specialist Agents for specialist work. Configure separate Agents for brand, legal, regulatory, and compliance domains. Each one tuned for its specific job. Each one called only when needed.
- AI quality matches the task. Different Agents can run on different models, picked for what each does best.
- Governance stays tight. Role-based access controls who can see, invoke, and approve Agent output. Full audit trails capture every decision.
- The platform grows with you. Aproove-built or customer-built Agents can be added, refined, and retired as your needs change.
Who it's for
- Compliance and regulatory teams in pharma, healthcare, financial services, Medicare and Medicaid marketing, where claim accuracy and disclosure language are non-negotiable.
- Brand and creative governance teams managing consistency across high-volume output.
- Legal review teams screening marketing material before public release.
- Operations leaders trying to scale review throughput without scaling headcount one for one.
Under the hood
AI-Powered Risk Detection runs against Aproove's structured file representation produced by the Processing Agent at upload. This includes file structure and metadata, pixel-level data, layered objects (where supported), text content, color values, and embedded elements. AI Agent invocation is abstracted from the underlying model provider, allowing customers to configure the LLM per Agent, including OpenAI, customer-provided enterprise endpoints, or Aproove-tuned custom models. Each Agent operates as an assistive tool within Aproove's governance framework: human-in-the-loop authority, role-based access control by user, role, or team, full audit trail of AI-assisted actions, and configurable enable/disable controls by project or asset type. AI requests transmit only the minimum necessary structured data over encrypted channels. Inference is transactional, scoped to the invocation context, and not used for upstream model training when running through enterprise endpoints.
Built for regulated environments where failures create real risk
Insurance, healthcare, and enterprise teams face unique approval challenges. Aproove handles state-by-state variations, mandated language, FDA submissions, and multi-geography brand governance without breaking a sweat.
Trusted by leaders
Used by teams that cannot afford uncertainty in their approval process.
"Implementing Aproove has dramatically reduced errors, increased motivation and satisfaction across the teams and importantly, saved the operation significant hard costs."
“The Aproove team are the best team in the world. I feel like I'm their only customer, they are always there for me.”
"Within a short period, we were able to reduce 25 workflows into a single workflow. The team saw a 15-week reduction in getting new marketing packages from idea to market. More importantly, it ensured that all the packages were compliant with regulatory requirements. All steps, comments, and approval are captured and saved for any audits."
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