interos.ai

interos.ai is on a mission to help federal agencies see what they've been missing. Big news launching soon. Knox Systems, Inc.

A major U.S. retailer runs thousands of stores and clubs, with locations sitting within 10 miles of almost 90% of the country's population. Each of those sites relies on its own network of suppliers. Standard views of locations or suppliers alone can overlook whether a site is truly resilient. Two sites that appear independent on the surface may actually pull from the same supplier corridor, putting them both at risk during the same disruption. Using interos.ai, this retailer visualizes supplier risk by geography, weighing exposure across existing and planned stores, offices, warehouses, and contingency sites. This geographic risk intelligence now shapes decisions on new store openings, backup capacity planning, and sourcing shifts, and feeds into FEMA-aligned response planning for events like Sandy, Katrina, Helene, and Milton. Supplier risk isn't only about sourcing decisions. At this scale, it becomes a matter of location strategy. See how interos.ai converts hidden exposure into clear, prioritized next steps: https://lnkd.in/evc9aBzs

Iran's drones hit two AWS data centers in the UAE and one in Bahrain this spring. An Oracle facility in Dubai was bombed a month later.    Data centers are now targets in active warfare and AI risk just became a geography problem.    In her latest piece for The AI Journal, Dr. Andrea L., SVP, Applied AI at interos.ai, breaks down what most risk teams are missing:    → 80% of global data center capacity faces heightened exposure to flood, fire, or drought  → 18% sit in extreme risk zones, concentrated in the U.S., Brazil, Australia, China  → A Super El Niño now has a 96%+ chance of persisting into 2027     Read Andrea's full piece: https://lnkd.in/e-uW3QQC

Oftentimes, there’s more below the people conflict that surfaces in the workplace, whether that’s unclear lanes, competing priorities, or other frictions. Making sure you have the correct systems and processes in place can help mitigate ongoing conflict rooted in these issues. Our CPTO Yardley Pohl added to the conversation with Forbes Technology Council, weighing in on the product teams versus governance departments conflict. She shared how sequencing and better timing between the two teams can help bring alignment to innovation and compliance as priorities. Read her full take below: https://lnkd.in/djr6FfbR

Supplier onboarding took one leading hyperscale data center provider 42 days. That's 42 days of exposure across a 1.6M-supplier ecosystem, with capacity delivery on the line the entire time. The old process meant fragmented, multi-tier supplier risk review and no way to know which supplier pathways could actually threaten site delivery, commissioning, or uptime. With interos.ai, that changed. The provider mapped its extended supplier ecosystem, prioritized 14,567 high-risk suppliers by project impact and substitution difficulty, and cut supplier onboarding from 42 days to 11. As their Risk & Procurement team put it, interos.ai turned "fragmented, multi-tier supplier risk management into a single, continuously monitored source of truth." With $6.7T in global data center capex projected by 2030, supplier visibility isn't a nice-to-have. It's capacity-delivery control. See how interos.ai turns hidden exposure into prioritized action: https://lnkd.in/g9h3qUEu

Most consumers never see where their products actually come from. Neither do most companies. Forced labor doesn't show up on a supplier scorecard. It hides in the sub-tier, past the point most risk programs ever look. By the time it surfaces, the goods have already reached the market. interos.ai's CPTO, Yardley Pohl, shared her perspective for Forbes Technology Council on how AI-driven analysis of import, shipping, customs, and trade data can flag forced labor risk deep in the supply chain, before it becomes a headline. But the technology only works if the visibility does too. Scaling this responsibly means transparent data sourcing, mapping beyond direct suppliers, and human review on every flagged case. Read Yardley's full take: https://lnkd.in/eqzWfuq3

Customer interactions are most frequently prioritized by the risk they pose, but today AI is shaping this part of the customer experience before a human ever interacts with it. Our CPTO Yardley Pohl shared her perspective in a new Forbes Technology Council roundup on the process of pre-framing risk by triaging requests through AI. Her take is that when AI flags a vendor, transaction or customer as "urgent" or "routine," that risk framing is then inherited by the human analyst reviewing the case. Read Yardley's full take here: https://lnkd.in/eRK9qqN4 #CustomerExperience #RiskIntel #AI

Nearly 80% of global data center capacity now faces heightened exposure to natural hazards. Our SVP of Applied AI Dr. Andrea L.’s latest article for The AI Journal breaks down the current risk landscape, from a strengthening El Niño to geopolitical instability targeting AI infrastructure. She explains how the physical footprint of the AI race has become just as critical as the digital aspects. Read her full analysis here: https://lnkd.in/e-uW3QQC #AI #SupplyChain #Resilience #DataCenters

Visibility told you where the risk was. Monitoring told you when it changed. Neither one told you what to do about it. That gap, between knowing and acting, is where most disruption actually happens. Reactive risk management means finding out about a problem after it's already touched your supply chain, your revenue, your timeline. The next era of third-party risk management isn't more dashboards. It's intelligence that arrives early enough to act on, with systems that act alongside you. Learn how interos.ai closes that gap: https://lnkd.in/eiUxMVBJ #SupplyChain #SCRM #AI

As we head into the long weekend, we're thinking about the workers who keep everything moving, on factory floors, in data centers, across logistics hubs, and in boardrooms. Supply chains run on people. This weekend, we're grateful for all of them. Happy Labor Day!