AI agents monitor hundreds of legal and regulatory sources around the clock, detect exactly what changed between one version of a document and the next, and score the likely business impact. Your domain experts make the call that matters.
Across every market an organisation operates in, someone is responsible for watching the law change. The work is essential and it is almost entirely manual.
Each country keeps its own list of trusted sources: government portals, legal journals, regulatory websites. Expert hours go into checking rather than interpreting.
Nothing moves until a compliance professional has read it and judged it relevant. Passing low-impact items downstream floods everything behind it, so the filter stays one document at a time.
The operational impact is assessed, then translated into functional tickets for product and business tickets for client-facing teams. Same change, two write-ups.
Every new jurisdiction adds the same manual load. Thresholds drift from one country to the next, and the reasoning stays in the heads of the people doing the checking.
A change caught late becomes an implementation done late, and in regulated services that reaches clients before it reaches the roadmap.
Faktion partnered with SD Worx to build a production-grade Legal Watch platform: agentic AI that scans hundreds of sources, detects regulatory changes, and assesses business impact per domain, so legal experts focus on judgment, not legwork.
We did not want to remove the domain experts. We wanted to give them a tool.
Five steps, done in sequence. Each one makes the next one more effective:
Continuously scan the sources that matter, across formats and jurisdictions. Some publish structured feeds. Most do not, so a scraping engine renders complex pages the way a browser would, works through nested repositories and anti-bot measures, and returns clean structured output. Scheduled per source, run automatically, with notification in-app and by email.
Filter the noise, so only what actually applies surfaces. AI agents classify each document against your own domains and score how likely it is to affect the business, with the reasoning attached to the score.
Version every change, so you see precisely what moved and when. New version against previous version, down to the clause, with the original rendered in-page and amendments highlighted. Summaries in the source language and in English.
This is the step a subscription cannot do. A legal update service tells you the law changed. It has no view of your products, your markets or your clients, so the translation from "this changed" to "this is what it means for us" lands back on your experts every time. The engine carries that mapping, built against your domains and your impact criteria, and your experts confirm or correct it.
Turn the assessment into the next step, and connect it to the systems where the work already happens.
Human judgment stays in the loop by design. The engine does the scale. People do the decisions. Steps one and three are mechanical and repetitive. Automating them returns expert attention to the question only a domain specialist can answer.
Add, update or retire sources through the interface, with scrape frequency set per source. The platform flags a source the moment it breaks or goes stale, before a gap opens in your coverage.
Single sign-on, with users assigned by country, domain and role so each person sees only their subset. Every status change and intervention is logged, which is what makes a decision defensible months later.
Countries and domains are added at any time without losing historical data. An evaluation dashboard shows how the AI is performing by type, so accuracy is monitored rather than assumed.
Add, update or retire sources through the interface, with scrape frequency set per source. The platform flags a source the moment it breaks or goes stale, before a gap opens in your coverage.
Single sign-on, with users assigned by country, domain and role so each person sees only their subset. Every status change and intervention is logged, which is what makes a decision defensible months later.
Countries and domains are added at any time without losing historical data. An evaluation dashboard shows how the AI is performing by type, so accuracy is monitored rather than assumed.
Producing a system that summarises legislation impressively is not the hard part. Producing one that does it reliably, across languages, across domains, on documents nobody has seen yet, is a different engineering problem.
Input samples paired with human-validated outputs, maintained by business users through the platform rather than by developers through scripts.
Specialised prompts judge the system's output against domain checklists your experts define, weighted so the criteria that matter most count for more. Users see the score and can open the reasoning behind it.
Every model call logged: prompt, cost, latency, output, feedback. When behaviour shifts, you can see where and when.
Business users draft and test changes in a safe environment. Promotion to production runs through approval and version tracking.
The architecture is domain-agnostic. What changes between deployments is the source list, the taxonomy and the impact criteria.
The same engine that tracks payroll legislation extends to adjacent domains such as data protection and anti-money laundering with adapted terminology and prompts.
Where legislative change across markets drives product changes and client communication directly
Where regulatory horizon scanning is a supervisory expectation
Where product compliance depends on tracking substance restrictions and labelling rules across markets
Faktion has spent nearly a decade building AI products that reach production and stay there. We partner closely with domain experts, because in regulated work they are the part of the system that cannot be automated away.