Kindo

The Use Case That Proves AI Will Change the World: Okay -- bear with us here. This is a fairly long post, but if you stick around to the end you'll find some gold. Setting the stage: 1. We recently were on site with a new enterprise client. 2. We spent 30 minutes training several dozen employees on the basics of AI. 3. Those employees then broke out into small groups to build Agents in www.kindo.ai . They were asked to focus on building Agents that would help them in their day-to-day life. Nothing fancy...just reduce your cognitive load. A brief backgrounder on the employees: 1. All "non-technical" 2. On a scale of 0-10 of knowledge of C##, Javascript, Python, Ruby on Rails, etc. they would average 0. 3. All very smart people, just not possessing coding skillsets. 4. Most had never used AI prior to this event. What absolutely wowed us: 1. This group came up with about 10 Use Cases that they solved using Kindo; they were all impressive. We're not taking anything away from the other 9 use cases they solved. 2. HOWEVER, one particular problem and solution leapt out at us during the presentation stage of the event. AND IT FLOORED US. 3. Namely, one of these employees had a persistent problem. 2. They work for a multi-national company with several global locations. 3. This employee is responsible for keeping the snacks in all these locations, using multiple different languages, properly stocked. And they are responsible for maintaining global employee morale by responding to localized requests for legacy and new snack inventory availability at multiple locations. 4. Ignoring all the ways they have tried to solve this in the past and have failed, the bottom line is after years of process and technology efforts to improve this process, they still spend about 1 hour per week in their efforts on this front. 5. This employee used AI (and Kindo, specifically) to build an AI Agent that reduced this time to 3 minutes per week. OK...so why did this floor us?: 1. This employee was given basic training in AI....maybe 30 minutes max. 2. This employee, in the course of 20 minutes, built an Agent in Kindo that saves them approximately 1 hour per week for infinity. (Talk about ROI) 3. They built it themselves. 4. They used multiple different LLMs and features in the Kindo platform to do it. Image to text, text to text, inclusion of contextual knowledge in the form of one-shot training via prompting, etc. (sorry...nerding out here....) Why does this matter?: 1. This employee now has access to secure AI, and a basic understanding of how to use it. 2. They have greatly reduced their workload in this task area, leaving them all that extra time to do higher-reasoning work. 3. They built this particular use case in 20 minutes...one can only assume that they'll build dozens more in the coming months that will result in similar ROI in other areas of their work. 4. Imagine what this means when the several thousand employee base of this company does the same thing.

Stay on top of #EndpointSecurity and #NetworkMonitoring news from the week of December 20th with this round-up of announcements from Appdome, Arctic Wolf / BlackBerry, Aviatrix, Kindo, and NETSCOUT. #endpoint #netmon #cybersecurity #cybersecuritynews #newsroundup #appdome #arcticwolf #blackberry #aviatrix #kindo #netscout

Don't get locked in. Deloitte Legal explores this and other key risks to address in contracts when procuring GenAI systems from vendors (see page 9): 1\ Be cautious of data privacy Clearly define data processing scope, limit it to what’s necessary, and allocate security and compliance responsibilities between the GenAI provider and the deploying organisation. Involve privacy officers early. 2\ Avoid the negative consequence of unlawful training data Understand the GenAI training data. If not publicly available, request details with contractual assurances about its provenance from the vendor. Consider requiring indemnity for breaches or third-party claims. 3\ Make sure your data is not misappropriated Clearly define what the GenAI vendor can do with inputs and outputs, ensuring alignment with intended use cases and data permissions. The vendor should also implement measures to restrict unauthorized access to inputs and outputs. 4\ Do not let costs get out of hand To maintain cost efficiency in GenAI procurement, it is important to consider long-term price stability and minimum volume commitments in a rapidly evolving market. 5\ Keep an eye on interdependencies with sector regulation Consider including clauses requiring vendors to support ongoing compliance with sector-specific legal and regulatory obligations, including regular audits, updates, and transparent communication. 6\ Liability Allocate risks (both internal and external) and responsibilities between parties through indemnities, warranties, and liability caps, including any third-party impacts, such as on end customers. 7\ Check your Environment, Social and Governance (ESG) policies Review your ESG policies and incorporate them where relevant into the GenAI contract, either directly or by reference. Account for their evolution throughout the contract’s duration. 8\ Don’t get locked in The organisation should assess if the contract locks them into the GenAI vendor, through long terms, minimum volume commitments, unfavourable termination rights, or lack of exit support. 9\ Keep cybersecurity in mind Organisations procuring GenAI systems should address both GenAI-specific and general IT risks. The organisation may need to delegate obligations to the vendor or rely on their support to meet certain regulatory requirements. Deloitte's 25-page report also covers managing GenAI risks in the supply chain, the EU AI Act’s impact on GenAI contracts, and putting theory into practice (see page 23). P.S. Report below & linked in comments. --- ♻️ Repost to help your network level up! 📌 Want more enterprise insights like this? Get on the list: https://lnkd.in/eJ6QQeru