INVA-AI-HERALD - ☁️ Google Cloud Turns Modernization Into an AI-Agent Job
INVA-AI-HERALD
📰 AI NEWS
1. 🇫🇷 Mistral Unleashes 1-Trillion-Parameter “Le Chonk”
📰 WHAT HAPPENED !!
Mistral AI has launched the public preview of Mistral Large 4, code-named “Le Chonk,” a new open-weight multimodal model with 1.05 trillion total parameters and 49 billion active parameters. The model uses a Mixture-of-Experts architecture and includes a 1.6-billion-parameter vision encoder. Mistral says it was trained on its own European infrastructure and targets demanding workloads including coding, cybersecurity, finance, manufacturing, geospatial analysis and chip design. The model supports a 1-million-token context window, while the company plans to publish its weights after the preview period.
🧠 WHAT CAN IT DO?
Mistral Large 4 can process text and visual information, handle long-context workloads and perform complex reasoning across coding, finance, cybersecurity and technical domains. Its sparse architecture activates only part of its enormous parameter count for each request.
🌍 REAL-WORLD APPLICATIONS
- Software development: Handle complex coding workloads.
- Cybersecurity: Analyze security problems and defenses.
- Engineering: Support technical and industrial workflows.
- Research: Process massive multimodal information collections.
2. ☁️ Google Cloud Turns Modernization Into an AI-Agent Job
📰 WHAT HAPPENED !!
Google Cloud launched Google Cloud Modernize, an end-to-end portfolio designed to use AI agents across enterprise infrastructure and application modernization. It combines existing migration services with new agentic capabilities, including an EKS-to-GKE Migration Agent and a new Modernization Hub where developers can analyze source code and map dependencies. Google is also adding AI-powered infrastructure assessment through Migration Center, allowing teams to model costs and modernization scenarios conversationally. The approach is aimed at shrinking lengthy modernization programs by using AI throughout assessment, migration and application transformation rather than treating AI as a separate add-on.
🧠 WHAT CAN IT DO?
Google Cloud Modernize uses AI agents to assess infrastructure, analyze applications, identify dependencies and assist with migration and modernization tasks. Its conversational tools can also build cost models and compare infrastructure scenarios without extensive manual spreadsheet work.
🌍 REAL-WORLD APPLICATIONS
- Cloud migration: Assist companies moving workloads.
- Legacy modernization: Analyze aging applications.
- Cost planning: Model infrastructure choices.
- Enterprise IT: Automate complex transformation workflows.
3. 🏭 ServiceNow Builds an AI Factory for Enterprise Workflows
📰 WHAT HAPPENED !!
ServiceNow launched AI Workflow Factory alongside Autonomous Engineer, creating a system designed to continuously discover, build and improve AI-powered enterprise workflows. The platform connects process mining, AI development and workflow execution into a single loop. Instead of launching separate AI projects whenever a business problem appears, companies can identify a measurable outcome, have AI-assisted tools build workflow improvements, deploy them and then refine the process based on results. ServiceNow says the system is governed through its AI Control Tower, giving organizations visibility and control over AI workflows and agent actions as automation expands across departments.
🧠 WHAT CAN IT DO?
AI Workflow Factory can identify processes suitable for AI improvement, help generate workflow changes and deploy them across enterprise operations. Autonomous Engineer assists with planning, coding and testing, while governance controls oversee agent actions.
🌍 REAL-WORLD APPLICATIONS
- Enterprise operations: Continuously optimize workflows.
- Software development: Automate planning and testing.
- Customer service: Improve case-handling processes.
- Governance: Monitor enterprise AI activity.
4. 🧠 Reflection AI Launches Beam to Challenge Open-Model Leaders
📰 WHAT HAPPENED !!
Reflection AI has unveiled Beam, its first open-weight model, positioning it as a competitor to leading Chinese open models while targeting efficient coding and agentic workloads. Beam contains 501 billion total parameters but activates about 23 billion per task, allowing the system to use a much smaller portion of its network during inference. The startup is focused heavily on software-development agents and wants developers to build systems that can perform longer sequences of technical work. Beam's arrival adds another major US-backed effort to the open-model race, particularly around models designed to deliver strong capability without requiring every parameter to run on every request.
🧠 WHAT CAN IT DO?
Beam is designed for coding and agentic tasks while using sparse activation to reduce the amount of computation required per request. That architecture aims to deliver large-model capability while keeping inference comparatively efficient and economical for developers.
🌍 REAL-WORLD APPLICATIONS
- Coding agents: Automate software-development tasks.
- Open AI: Give developers more model-control options.
- Enterprise agents: Run longer technical workflows.
- Inference: Reduce unnecessary computation per request.
5. 🖥️ Ghost Wants to Put a Private AI Brain on Your Desk
📰 WHAT HAPPENED !!
Startup Ghost emerged from stealth with $11 million in seed funding and introduced Core, a $3,499 screenless personal computer built specifically to run AI agents locally. Core includes an NVIDIA RTX Pro 4000 SFF Blackwell GPU, preinstalled AI models, its own software layer, browser and file system, and is designed to continuously process personal information and tasks. The company says personal memory and models can operate locally, with encrypted information and controls over how much autonomy agents receive. Ghost is betting that future personal AI will live on dedicated hardware rather than inside ordinary computers or cloud-only assistants.
🧠 WHAT CAN IT DO?
Core can continuously run AI agents that work with desktop information, applications and other connected devices. Models can operate locally, users can load additional models, and an agent firewall is being developed to monitor potentially risky network actions.
🌍 REAL-WORLD APPLICATIONS
- Personal AI: Keep AI processing close to the user.
- Automation: Run agents continuously.
- Privacy: Store models and personal memory locally.
- Productivity: Let agents perform multi-step tasks.
6. 🚗 Flai Raises $27M as AI Starts Running Car Dealership Follow-Up
📰 WHAT HAPPENED !!
Flai raised $27 million in Series A funding as its AI platform expands from answering dealership phone calls into a broader automated customer-engagement system. The company's software now handles customer conversations, outbound campaigns, follow-ups and appointment scheduling across sales and service operations. Flai says its technology is being used by more than 10 of the country's top 50 dealer groups and is booking around 50,000 appointments per month. Revenue has reportedly increased 20-fold over the past year. The new funding will support expansion as dealerships increasingly use AI to manage customer communication throughout the vehicle-buying and servicing journey.
🧠 WHAT CAN IT DO?
Flai's AI agents can answer customer questions, make outbound calls, follow up on leads, schedule appointments and alert dealership leadership when human intervention is needed. The system is evolving toward an AI-powered customer-management platform built specifically for dealerships.
🌍 REAL-WORLD APPLICATIONS
- Car sales: Follow up with potential buyers.
- Service departments: Schedule maintenance appointments.
- Customer support: Handle routine conversations.
- Dealership operations: Surface issues requiring human attention.
7. 🏦 Valon Raises $150M to Put AI Agents Into Mortgage Servicing
📰 WHAT HAPPENED !!
Mortgage technology company Valon raised $150 million in Series D funding at a $2.3 billion valuation to expand its AI-native ValonOS platform. The company wants mortgage servicers to move away from fragmented legacy systems and use a unified operating environment where AI agents can perform regulated servicing tasks. Valon says the platform can manage loan data, investor reporting, compliance logic and money movement while agents handle activities such as homeowner communications and escrow analysis. The financing will support product development and hiring as Valon expands its deployment among large mortgage-servicing organizations and pushes AI deeper into a highly regulated financial workflow.
🧠 WHAT CAN IT DO?
ValonOS brings mortgage-servicing operations into one platform while AI agents automate repetitive tasks such as customer communication, escrow analysis and operational processing. The system is designed specifically for regulated finance rather than general-purpose office automation.
🌍 REAL-WORLD APPLICATIONS
- Mortgages: Automate recurring servicing tasks.
- Finance: Process regulated operational workflows.
- Customer service: Handle homeowner requests.
- Compliance: Support complex financial operations.
8. 📦 Procuros Raises €20M to Let AI Agents Run B2B Trade
📰 WHAT HAPPENED !!
Hamburg-based Procuros raised €20 million in Series A funding to build infrastructure for AI-native supply-chain connectivity and autonomous B2B trade. The company is tackling a fragmented business environment where companies exchange orders, invoices, shipping information and other documents through EDI systems, individual integrations and manual processes. Procuros is developing a connectivity layer that lets businesses exchange this information through more standardized infrastructure while enabling AI agents to participate in trading workflows. The new investment will support international expansion, growth of its go-to-market organization and development of additional AI capabilities designed to automate more steps across business trading networks.
🧠 WHAT CAN IT DO?
Procuros connects trading partners and structures business documents so software agents can interact with supply-chain workflows. Its AI-native infrastructure aims to move B2B transactions from manually managed integrations toward increasingly autonomous processes.
🌍 REAL-WORLD APPLICATIONS
- Supply chains: Automate document exchange.
- Procurement: Streamline purchasing workflows.
- B2B commerce: Connect trading partners.
- AI agents: Enable autonomous business transactions.
🔥 CURRENT TRENDING AI NEWS
9. 🛡️ SailPoint Gives AI Agents Their Own Security Guardrails
SailPoint unveiled a major expansion of its identity-security platform with Autonomous Agents, Autonomous Identity Security Posture Management and enhanced Agentic Fabric capabilities. The system is designed to discover hidden AI agents, map their credentials and permissions, continuously identify identity exposures and automatically remediate certain risks. SailPoint is also introducing policy-driven controls, temporary access and an agent kill switch, allowing organizations to stop suspicious AI activity rapidly. The broader push reflects a growing enterprise problem: autonomous software agents can now act through privileged identities, creating a new security layer that must be governed alongside humans, applications and traditional machine accounts.
10. 🔧 UpSmith Raises $10M to Turn Missed Contractor Leads Into Jobs
UpSmith raised $10 million in Series A funding to expand its AI platform for electricians, plumbers, HVAC companies and other trades businesses. Its AI agents are designed to answer calls, book jobs, follow up on estimates, renew memberships and reconnect with customers who previously stopped responding. The company says its systems have already helped contractors recover significant revenue opportunities from missed calls and unsold estimates. The new capital will fund engineering, distribution and additional product development as UpSmith pushes AI deeper into the traditionally fragmented home-services industry, where automation can directly influence bookings, customer retention and contractor revenue.
11. 🛴 Nearhuman Brings Physical AI Onto E-Scooters
Bristol startup Nearhuman has raised £350,000 in pre-seed funding to develop on-device AI safety technology for shared e-scooter and e-bike fleets. Its system combines edge computing, computer vision and human-centered design to identify road and pavement-related situations directly on the vehicle. The startup is already running a live pilot in Bristol, where its technology is being tested under real operating conditions. Rather than sending every video stream to the cloud, Nearhuman is focused on intelligence running at the edge, giving operators and cities more immediate information about how micromobility vehicles are being used while keeping privacy considerations built into the hardware.
12. 🧩 Zeroset Raises $5.2M to Give AI Agents a Memory of How Companies Work
Zeroset emerged from stealth with $5.2 million in pre-seed funding for Nebula, a platform designed to help AI agents understand how organizations actually operate. Nebula connects workplace systems such as Microsoft 365, Outlook, Teams, SharePoint and GitHub and tracks how information, activities and decisions evolve over time. Instead of simply retrieving documents, the system attempts to give agents a picture of recurring business workflows and how situations were handled previously. That could help autonomous agents make better decisions when company knowledge is scattered across multiple systems, a major challenge as enterprises move from simple AI assistants toward agents capable of executing complex work.
🧩 AI TOOLS
📱 iphone-use
An open-source tool that lets AI agents see and control a real iPhone through a Mac, enabling automated taps, typing, scrolling, screenshots, and repeatable phone workflows.
🗓️ Chunk
A macOS time-blocking workspace that combines tasks and calendars, helping you turn your schedule into focused work blocks while also letting AI manage your plan through MCP.
📈 Extrovert
An AI-assisted LinkedIn outreach tool that finds useful prospect signals, drafts personalized comments and messages, and helps maintain relationships with leads with less manual work.
🛠️ Brnch
A modern code-hosting environment designed around AI-assisted development, giving coding agents a workflow for working with repositories and shipping software.
🎨 EasyCut
An editing tool built around AI-generated motion-video workflows, making it easier to refine and edit animated videos created with coding-oriented AI tools.
📞 LeadPatrol
An AI missed-call recovery tool for service businesses that instantly texts callers, answers common questions, captures lead details, and helps turn missed calls into qualified opportunities.
🌐 Rill Browser
A new Mac browser built around Claude Code and Codex, letting coding agents work alongside your browsing so you can start tasks directly from the pages you visit.
🧠 Willow Knowledge
A new context layer for Willow that imports your writing style, preferences, and personal context from the AI assistants you already use, helping its writing assistant produce more personalized messages.
🎧 Doco
A new AI music product designed to create music that fits the context of a company, giving teams a way to generate more suitable audio for their brand and content.
🧑💻 Cosmic AI Support Agent
A new website support agent that answers visitor questions using the content already published on your site, with answers updating as your website content changes.
🧠 PROMPT OF THE DAY
Turn a Screenshot Into a Personal How-To Guide
Important Note: You’ll need to use the prompt below to get the complete result.
What This Prompt Does
Ever save a screenshot and later forget why you saved it? Give AI the screenshot plus your goal, and it can turn the visible information into a clear, personalized guide—with what matters, what to do next, and what information is still missing.
📋 The Prompt
Act as my visual information assistant.
I will provide a screenshot, photo, or screen capture. Your job is to understand what is visibly shown and turn it into a practical guide for my specific goal.
MY IMAGE:
[Upload or attach the screenshot/photo]
WHAT I WANT TO ACHIEVE:
[Describe what I am trying to do]
MY EXPERIENCE LEVEL:
[Beginner / Intermediate / Advanced]
MY CONSTRAINTS:
[Time, budget, device, skill level, or other limitations]
First, identify only the information that can reasonably be understood from the image.
Then provide:
1. WHAT I’M LOOKING AT
Briefly explain the important elements visible in the image.
2. WHAT MATTERS FOR MY GOAL
Filter out information that is not relevant to what I’m trying to accomplish.
3. STEP-BY-STEP GUIDE
Give me the simplest practical sequence of actions based on the visible information.
4. WATCH OUT
List up to 3 mistakes, confusing points, or things I should double-check.
5. MISSING INFORMATION
Tell me exactly what cannot be determined from the image and what additional information would be needed.
6. NEXT ACTION
Give me the single best thing to do first.
RULES:
- Do not invent text, buttons, settings, prices, features, or information that cannot be clearly identified.
- If something is unreadable or uncertain, say so.
- Do not assume that a visual element works a certain way unless the image supports it.
- Keep the instructions beginner-friendly and practical.
- Prioritize my stated goal over describing irrelevant parts of the image.🧪 Try It With
Upload a screenshot of a software settings page and write:
“I want to improve my video quality without making the file size too large. I’m a beginner.”
🎯 What You’ll Get
A confusing screenshot becomes a personalized mini tutorial: what you’re seeing, which parts matter, what to do, what to double-check, and the exact first step to take.
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