Akkodis is making the case that AI transformation isn’t theoretical anymore—it’s happening inside factories, banks, and enterprise IT teams today. The global digital engineering and consulting firm has announced a string of successful implementations that illustrate how its AI and data solutions are delivering measurable impact at scale.

The message is straightforward: AI isn’t just a capability; it’s becoming core infrastructure. And Akkodis is positioning itself as the partner that turns AI ambition into enterprise-wide change.

AI That Compresses Days Into Seconds

One of the most striking examples comes from a global healthcare manufacturer wrestling with production scheduling. Historically, syncing supply forecasts with manufacturing capacity took five days of manual work. Using Akkodis’ combinatorial optimization engine—and a human-in-the-loop review layer—the company cut that to seconds.

The next phase introduces LLM-based agents allowing managers to describe production priorities in plain language. If successful, scheduling could shift from reactive to predictive, offering a real competitive edge in an industry where precision and reliability matter.

Teaching Banks to Use AI Responsibly

AI transformation often fails not because the tools don’t work, but because teams don’t know how to use them. Akkodis addressed this challenge through a partnership with Microsoft Worldwide Learning and the Commonwealth Bank of Australia.

Through tailored bootcamps, webinars, and hands-on AI training, engineering teams rapidly learned how to apply tools like GitHub Copilot. Roughly 30% of AI-generated code was accepted—an early indication that AI can enhance accuracy and speed when applied responsibly. For a sector where governance and compliance are non-negotiable, this approach offers a repeatable blueprint.

Automating Enterprise IT at Scale

Akkodis Japan delivered another notable case study: a generative AI and low-code program that helped 2,000 employees become proficient in AI tools within 10 months. The effort saved more than 15,000 hours annually by automating claims submissions and sales processes—workstreams traditionally plagued by repetitive tasks and human bottlenecks.

This internal success now serves as a template for clients looking to scale automation responsibly without losing oversight or quality control.

A Blueprint for Responsible AI Transformation

Akkodis argues that these outcomes highlight a broader truth—AI is only as powerful as the human expertise, governance, and change management that support it. The company calls this framework Akkodis Intelligence, a philosophy that blends domain experience with advanced technology to ensure AI deployments create sustained, measurable results rather than isolated wins.

Akkodis Group AI Officer Joshua Morley emphasized this point, noting that businesses need “confidence and capability” as much as they need technical horsepower. Responsible AI isn’t just an industry promise; it’s fast becoming a competitive differentiator.

What It Means for the Market

These examples underline a growing shift across sectors: AI transformation is moving out of pilot projects and into full operations. Healthcare, financial services, and enterprise IT all face intense pressure to improve efficiency, reduce errors, and accelerate decision-making. Solutions that combine speed with responsible governance are quickly becoming the industry’s preferred path.

Akkodis’ recent projects show how combining human insight with machine intelligence can compress timelines, elevate quality, and unlock new operational capacity. With more AI-driven products planned in the months ahead, the company is preparing for a wave of demand from organizations trying to modernize without compromising control.

For industries seeking practical AI—with real impact, not hype—Akkodis is positioning itself as a partner that delivers transformation that lasts.

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Artificial intelligence may be reshaping global industries, but small and mid-sized businesses face a different constraint: time. That’s the gap Halper AI, founded by Eduard Gevorkyan, aims to eliminate. The newly launched platform positions itself not as another tool to manage—but as an invisible partner that quietly runs the operational backbone of a business.

Eduard’s background blends science, strategy, and product innovation. Trained in biochemistry and biomedical engineering, he started his career at McKinsey & Company before moving to Google, where he specialized in data-driven product design. His entrepreneurial profile solidified in 2023 with the launch of SoulsHub, a Barcelona-based platform offering AI-powered replicas of mentors and coaches. The product grew to more than 200 AI personalities and was acquired a year later by a Saudi tech group for an estimated €5–10 million.

An Invisible Business Manager for Overworked Owners

With Halper AI, Eduard shifts focus from knowledge platforms to day-to-day business survival. Many owners spend more time managing logistics than serving clients. Halper operates as an AI Business Manager that automates communication, bookings, invoicing, and follow-ups, syncing with Instagram, WhatsApp, and calendar tools.

“Let others chase engagement. We’re chasing freedom,” Eduard says, capturing the platform’s philosophy in a single line.

The goal isn’t sticky engagement or dashboards. It’s relief.

A “Do Less” Approach to AI

Most digital platforms want users to check in constantly. Halper flips that model entirely. Eduard’s guidance is simple: “Please, don’t open Halper or open it once and close it.” The platform is built to run quietly in the background, ensuring clients get timely responses, schedules stay full, and invoices go out without fuss.

This design philosophy revolves around what Eduard calls “freedom metrics.” Silicon Valley values daily active users; Halper values time returned to the owner. Less screen time, more real time.

Why Halper Matters for SMBs

For small businesses where the founder is often the marketer, accountant, scheduler, and customer support team, Halper acts like an unseen employee. It gives a barber more time to refine a cut, a yoga instructor more attention to dedicate to students, or a local designer more hours to create.

At its core, Halper AI addresses the oldest challenge in business: balancing operations with growth. By absorbing the administrative load, it frees owners to focus on the part of their business that customers actually experience.

With simplicity, invisibility, and peace of mind as its guiding principles, Halper AI is redefining what effective AI looks like for SMBs—not more software, but less noise.

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mimik, the device-first AI pioneer known for its Continuum AI and agentic software platform, is expanding into the Middle East. The company signed a strategic MOU with UAE-backed investment entities Next71 Ltd and ASK Holding LLC to establish mimik UAE, a new joint venture focused on accelerating sovereign AI innovation across the region. The announcement, made during Abu Dhabi Autonomous Week, aligns with the UAE’s aggressive push to become a global center for advanced technology and AI sovereignty.

The move reflects directives championed by His Highness Sheikh Mohamed bin Zayed Al Nahyan and the Artificial Intelligence and Advanced Technology Council (AIATC) to build a future defined by national capability, autonomy, and next-generation digital infrastructure.

A New Model: Moving from Cloud-First to Citizen-First AI

mimik’s platform is built around decentralization—shifting intelligence away from centralized datacenters and toward the billions of devices that already surround us. That model resonated strongly with Next71.

“Together with mimik we are reimagining what’s possible,” said Sara Dhafer Alahbabi, Director of SPV and Portfolio Relations at Next71. She noted that mimik UAE will give regional industries the “autonomy, flexibility, and security” needed to advance the Emirates’ AI ambitions.

ASK Holding echoed the sentiment, emphasizing that this joint venture isn’t about adopting the next cloud trend—it’s about redefining where intelligence lives. The group described the shift as moving the UAE “from cloud-first to citizen-first AI—private, resilient, and real-time.”

Beyond the Cloud: The Distributed Intelligence Era

The UAE’s partnership with mimik underscores a decisive pivot away from traditional cloud-centric AI. Instead, the joint venture will enable distributed intelligence across devices, vehicles, manufacturing hubs, ports, logistics networks, and entire cities. Every node—whether a robot, sensor, or mobile device—can process, communicate, and act independently.

This approach strengthens data sovereignty, reduces latency, boosts energy efficiency, and supports sustainability goals by minimizing reliance on massive cloud operations.

As the world shifts toward an agentic economy, defined by autonomous software agents and a future Knowledge-as-a-Service (KaaS) market expected to reach trillions in value, new infrastructure models are essential. That’s where mimik sees the opening.

“We are entering the age of the agentic economy,” said Fay Arjomandi, Founder and CEO of mimik. She called mimik’s distributed platform the “most valuable tech stack for the agentic-native economy,” offering control, operational autonomy, and sustainability-driven cost advantages.

Device-First Continuum AI: The Foundation of mimik UAE

At the technical level, mimik’s Continuum AI transforms any device—robotic arm, traffic sensor, industrial machine—into a self-aware, contextually intelligent node. These devices can:

• Process locally

• Act autonomously

• Collaborate with other devices

• Operate offline-first

• Seamlessly sync with cloud systems only when needed

The result is a living, adaptive intelligence mesh that supports everything from autonomous mobility systems to resilient industrial operations.

For Abu Dhabi, this architecture aligns directly with its vision of becoming the world’s premier hub for physical AI—where intelligence is woven into the infrastructure of everyday life, not restricted to remote datacenters.

Building the UAE’s Agentic Future

mimik UAE aims to serve as a catalyst for talent development, sovereign AI innovation, and new economic growth. By decentralizing intelligence at scale, the joint venture strengthens the region’s digital independence while accelerating adoption of edge-native, agent-driven technologies.

The partners share a broader ambition: to make Abu Dhabi a global leader in AI systems that are sustainable, autonomous, and deeply integrated into physical environments.

As governments and enterprises worldwide grapple with AI’s next era, the UAE is positioning itself early—and boldly—with device-first architecture at the center of its strategy.

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Nirmata, the company behind Kyverno and a major force in policy-as-code innovation, has released its AI Platform Engineering Assistant, a new AI-driven solution designed to automate Kubernetes security, compliance, and workflow governance across cloud, IaC, and hybrid environments. The launch comes at a moment when enterprises are racing to modernize infrastructure but struggling to keep platform engineering resources aligned with AI-accelerated development cycles.

Industry pressures are mounting. Software creation is scaling more than 30x faster thanks to AI-assisted development, while global AI infrastructure spending is projected to exceed $350 billion. Yet nearly half of enterprises report critical skills gaps in platform engineering. Nirmata’s answer is an assistant that turns Kubernetes governance—traditionally slow, manual, and error-prone—into a continuous, AI-powered system.

Automating the Bottleneck in Modern Infrastructure

“Platform engineering has become both the bottleneck and the enabler of the AI future,” said Ritesh Patel, Vice President of Product at Nirmata. Without reliable guardrails, teams risk scaling security vulnerabilities just as fast as they scale development. Patel argues that AI-powered governance is the only path to sustainable growth, and the new assistant is designed to enforce compliance without slowing innovation.

At the core of the assistant is Kyverno, the open-source CNCF project that has become a standard for Kubernetes and IaC policy-as-code. Nirmata layers a multi-agent AI architecture on top of Kyverno to automate policy authoring, detection, and remediation—while keeping humans in the loop for verification.

What the AI Assistant Can Do

The new system is built around three intelligent agents that streamline day-to-day platform engineering work:

Copilot Interface
A conversational assistant that turns complex troubleshooting into simple prompts. Engineers can ask questions in natural language and receive detailed insights, compliance reports, and recommended actions in seconds.

Policy-as-Code Agent
This agent converts natural language rules into validated Kyverno policies for Kubernetes and IaC. It reduces syntax errors, standardizes governance across clusters, and makes policy creation accessible even to teams without deep policy-as-code expertise.

Remediation Agent
When misconfigurations or policy violations appear, this agent identifies them, generates secure fixes, and validates them. Engineers remain in control but spend far less time diagnosing and resolving issues.

Together, the agents form a continuous, intelligent governance system for Kubernetes, reducing operational noise while strengthening compliance, security, and reliability.

Built for Multi-Cluster, Multi-Cloud Realities

The assistant supports all major Kubernetes distributions, IaC platforms, and CI/CD systems. Organizations running multi-cluster or hybrid-cloud environments can integrate it directly into existing developer workflows without restructuring pipelines.

For companies grappling with rapid AI adoption and complex infrastructure scaling, Nirmata’s platform offers a pragmatic approach: automate what slows teams down, enforce policies consistently, and free engineers to focus on higher-value innovation rather than manual security cleanup.

Nirmata’s new assistant signals a broader trend across the industry: Kubernetes governance is no longer just configuration management—it’s becoming an intelligent, autonomous layer of the modern software stack.

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TechnoMile is taking a decisive step toward redefining how government contractors manage growth, compliance, and the full federal lifecycle. At Elevate25, the company’s annual customer conference, TechnoMile introduced its fully re-architected TechnoMile Platform and a new wave of agentic, AI-driven product innovations designed to streamline everything from opportunity discovery to contract execution.

The announcements landed at a pivotal moment for the sector. Federal contractors face rising competition, shrinking margins, and increasingly complex compliance requirements. TechnoMile’s strategy is clear: put AI at the center of federal go-to-market and contract operations.

A Unified, AI-Native Platform for the Entire GovCon Lifecycle

The newly launched TechnoMile Platform serves as a secure, unified foundation connecting Growth, Portfolio Management, Contracts, Security, and Supply Chain teams in one environment. Unlike legacy tools retrofitted for federal workflows, the platform has been rebuilt from the ground up with AI embedded at every layer.

It integrates seamlessly with clients’ CRM and ERP systems—merging enterprise data with TechnoMile’s purpose-built federal contracting capabilities. Through domain-trained AI agents, the platform offers real-time insights, automated workflows, intelligent recommendations, and continuous adaptation based on organizational behavior.

A major differentiator is security: the platform meets FedRAMP Moderate Equivalency, enabling contractors to meet stringent federal cybersecurity standards without adding operational burden.

“We’re redefining how government contractors operate by embedding AI into the very fabric of their business,” said CEO Ashish Khot. He emphasized that the platform’s agentic automation helps clients work smarter, move faster, and unlock new levels of growth.

New Agentic Innovations for Growth and Contracts

TechnoMile also unveiled several AI-powered tools—some available now, others on the near-term roadmap—aimed at transforming federal business development, capture, and contract management.

GovSearchAI
A market and opportunity intelligence engine using agentic AI to surface high-value leads, perform rapid pipeline research, and deliver personalized opportunity insights. Growth teams can spend more time pursuing deals that matter.

Capture Copilot
A domain-trained AI agent that assists with research, past performance analysis, document drafting, and CRM updates across the capture lifecycle. The result is faster execution, reduced manual work, and more strategic focus.

Transform Copilot for Pre-Award
Designed to accelerate proposal development, this agent extracts business intelligence from solicitations, automates compliance workflows, and provides AI summaries and conversational document queries to help teams refine pricing and risk assessments.

Mila — TechnoMile’s New Digital Assistant
Mila brings conversational intelligence directly to Growth and Contracts teams, offering instant access to opportunity data, contract insights, executive briefs, and proposal artifacts. It behaves like a virtual BD, Capture, or Contracts Manager, speeding up decision-making across the lifecycle.

AI Agents for Contracts
These agents automate deliverable creation, approvals, document ingestion, and executive summaries. They enhance visibility, reduce errors, and strengthen performance across contract management.

Authoring & Negotiating Commercial Agreements
An extension of TechnoMile’s existing contracting capabilities, this tool uses Mila to guide clause selection, evaluate language, automate drafting, and enforce compliance with internal standards—streamlining commercial agreement workflows end to end.

Building an AI-Driven Future for Federal Business

The common thread running through TechnoMile’s announcements is a shift toward continuous, intelligent automation. By pairing FedRAMP-aligned security with domain-specific AI agents, the company aims to make federal contracting faster, more predictable, and significantly more efficient.

As government contractors navigate a landscape increasingly defined by data, regulation, and competition, TechnoMile is positioning its platform as the operating backbone for the next era of federal growth and contract execution.

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ArcadianAI is stepping into the center of the security world with a blunt message: the traditional monitoring model is breaking. Security operations across the U.S. and Canada pour millions into control rooms, staff, and infrastructure, yet human operators still miss incidents and burn out. Most camera feeds show nothing for hours, while the workload keeps rising. ArcadianAI says it has the answer—AI employees that work like trained guards but at machine scale.

Ranger: An AI Guard Built for Real-World Security Demands

The company’s flagship platform, Ranger, connects directly to existing CCTV and NVR systems, acting as a fully autonomous digital security guard. Ranger does more than detect motion. It thinks like a human operator, reads context, and understands which events matter.

It recognizes weapons, break-ins, theft, fights, fires, accidents, vandalism, loitering, and suspicious vehicles. Each incident is analyzed, scored, and sent to operators with location context and recommended actions. Instead of endless noise, monitoring teams receive filtered, high-value decisions.

Ben Kavousi, Vice President of Operations at Virtual Security Concierge, put it plainly: “One AI guard can monitor more than ten thousand cameras for less than one human operator watching sixteen.”

Scaling Security Without Scaling Labor

Human monitoring hits the same wall every time: more cameras require more people. That equation doesn’t scale. Ranger flips the model. It never loses focus, gets tired, or misses a detail. It watches thousands of feeds across multiple sites in real time. No hiring waves, no training cycles, no new control rooms. Just cameras and AI.

This shift is especially relevant as monitoring centers face tighter margins and rising contract demands. Ranger functions as a workforce multiplier—an AI teammate filling the gap between growing workloads and limited personnel.

Cutting Costs While Improving Coverage

Labor remains the largest cost driver in video monitoring. It’s also where most missed incidents originate. Ranger automates up to 95 percent of manual monitoring work, reducing false alarms and expanding coverage. It delivers continuous situational awareness across every camera feed, something no human team can match.

This moves monitoring companies from labor-heavy operations to lean, intelligent systems capable of scaling without burnout or quality loss. Ranger isn’t positioned as a software tool. It’s marketed as a true AI teammate.

Built for the Modern Monitoring Center

ArcadianAI designed Ranger as an open, flexible platform compatible with the tools monitoring centers already use.

Key integrations and capabilities include:

• Support for RTSP, ONVIF, SIP, H264, and H265

• Compatibility with 3,000+ camera models, including Hanwha, Axis, Hikvision, Avigilon, and Pelco

• Integrations with Immix, Sureview, DW Spectrum, and Brivo

• Cloud or hybrid edge deployment with no proprietary hardware

• REST API, Webhooks, and MQTT for VMS and PSIM workflows

• Built-in encryption, audit logs, and GDPR, CCPA, and SOC 2 compliance

• Modular AI policies for residential, commercial, industrial, and education sites

This makes Ranger a drop-in AI layer for existing infrastructure rather than a full-system replacement—one of the fastest paths to modernization for centers that can’t afford downtime.

AI as a Teammate, Not a Replacement

ArcadianAI frames its technology as collaborative, not disruptive. Founder Marie Roohi captured that sentiment: “AI is not the end of security guards. It is their strongest teammate.”

For an industry grappling with labor shortages, rising costs, and expanding camera networks, Ranger marks a clear shift toward an AI-first model—one that addresses the realities of today’s monitoring landscape without discarding human expertise.

ArcadianAI believes the future of security isn’t fewer guards. It’s smarter systems, stronger teams, and AI support that scales where people can’t.

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Landbase, the agentic AI startup reshaping how businesses identify, target, and engage customers, has been named to Gartner’s 2025 Cool Vendors in AI for Marketing list. The recognition highlights emerging companies delivering breakthrough applications of AI, especially those redefining how marketing and GTM teams operate.

The announcement marks a major milestone for Landbase, which has rapidly positioned itself as a new category leader in AI-driven audience intelligence and go-to-market execution.

A New Model: Turning Natural Language Into GTM Precision

Landbase built the first agentic AI platform for go-to-market, enabling teams to define ideal customers or markets using plain language. Instead of stitching together datasets, tools, and spreadsheets, users simply describe their intent. Landbase then instantly generates precise, high-fit audiences.

After creating these audiences, the platform’s AI agents enrich, validate, and activate them across channels—email, phone, and social—so campaigns begin with relevance instead of guesswork. The approach compresses what used to take days into minutes, giving marketing and sales teams a shared intelligence layer that keeps GTM motions aligned.

Leading B2B enterprises and fast-growing startups rely on Landbase to uncover new markets, surface hidden demand, and connect siloed workflows around a single view of audience fit.

“Agentic AI Is the Next Wave of Business Growth”

Landbase CEO and co-founder Daniel Saks called Gartner’s recognition a validation of the company’s core thesis: agentic AI and domain-specific models will define the future of business growth.

Enterprises may be swimming in data, Saks noted, but converting fragmented information into actionable insights still slows GTM teams. Landbase addresses that by pairing its proprietary GTM Omni models with agentic data and search workflows. The result is instant, high-accuracy predictions of who companies should target next.

“It’s about turning complex and fragmented data into simple, actionable intelligence that drives real outcomes,” Saks said.

A Platform Built for Speed, Accuracy, and Alignment

Landbase’s traction comes at a time when precision targeting has become essential. Budgets are under pressure. Conversion cycles are longer. GTM teams need more signal and less noise.

The GTM Omni model that powers the platform continuously learns from millions of real-world interactions. This improves prediction accuracy and audience quality over time, helping companies focus effort where conversion likelihood is highest.

Recent platform enhancements include:

• More powerful natural-language querying for audience exploration

• Audience validation tools to refine high-fit segments

• Collaborative AI agents that simulate GTM roles and streamline execution across targeting, qualification, and outreach

These capabilities reduce wasted spend and give teams a clearer path to measurable pipeline impact. As companies look beyond static databases and manual research, Landbase offers an adaptable system built for speed and intelligence—not spreadsheets and guesswork.

Landbase Emerges as a New Standard for AI-Driven GTM

The Gartner Cool Vendor nod reflects a broader shift in the market. Go-to-market teams now compete on accuracy, agility, and integrated intelligence. Landbase is positioning itself as the platform that brings all three together through agentic AI.

With its natural-language interface, predictive models, and cross-channel activation engine, the company is creating a new blueprint for modern audience strategy—one where GTM teams move faster, collaborate seamlessly, and engage only the buyers that matter.

As organizations push for smarter growth with fewer resources, Landbase is quickly becoming a foundational tool for AI-powered audience definition and execution.

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In a move that signals where enterprise marketing is headed next, Palantir Technologies and Stagwell have joined forces to launch a new AI-driven marketing platform. The partnership brings together Palantir’s Foundry, Code and Theory’s orchestration software, and The Marketing Cloud’s proprietary data stack to power a unified system designed for large teams that need precision, speed, and massive data agility.

The platform doesn’t just crunch numbers. It automates complex marketing workflows, optimizes audiences, and gives enterprises the ability to deploy AI “agents” that act on their data. For organizations handling millions of customer records, this kind of automation is no longer a nice-to-have. It is survival.

A Central AI Hub for Marketers Doing Business at Scale

The combined system is already in early use through Assembly, Stagwell’s media arm, as part of an MVP rollout for select U.S. clients. Stagwell plans to expand availability across its network in the coming months.

Enterprises that adopt the platform gain access to a central marketing hub capable of handling tasks like audience alignment, campaign management, and data appending. Instead of wrangling siloed systems, teams can run orchestration from a single environment that feeds intelligence back into their marketing workflows.

For companies buried under massive datasets, the platform promises clear visibility. It can sift through tens of millions of records to segment audiences, analyze behaviors, and surface insights before a campaign launches. The goal is simple: increase ROI by ensuring brands understand their customers long before any creative hits the market.

The platform will be offered as a standalone product, but Stagwell hints at broader applications beyond marketing—including supply chain analysis and network regionalization.

Leaders Call It a Turning Point

Alex Karp, CEO and co-founder of Palantir, positioned the partnership as a shift toward a more adaptive marketing future. “Our software supercharges the speed of metrics collection and revolutionizes data integration capabilities,” he said. According to Karp, that speed unlocks real value not just for Stagwell but for any enterprise needing cleaner, faster decision-making.

Stagwell CEO Mark Penn called the offering “the holy grail of marketing,” pointing to its blend of advanced targeting, AI automation, and measurable outcomes. Penn expects the initiative to evolve into a major revenue engine within The Marketing Cloud, projecting eventual returns in the hundreds of millions.

Early clients are taking notice. Jonathan Schottenstein, president of American Signature Inc., said the company is already piloting the platform. “We are very excited for the potential of what the model can unlock in better understanding our customers and helping to increase our effectiveness,” he noted.

Why This Matters in Today’s Marketing Landscape

Marketers have spent years chasing the promise of AI-driven efficiency. Most solutions either lacked data depth or couldn’t execute with enterprise-level security. Stagwell and Palantir appear to be solving both problems at once.

The inclusion of differential privacy technology adds another key layer, especially as marketers balance data personalization with growing regulatory pressure. Protecting customer information without sacrificing precision is becoming non-negotiable.

At a time when marketing budgets face stricter scrutiny, a platform that scores higher ROI before a campaign launches could give brands a much-needed advantage. If Palantir and Stagwell deliver on their claims, this partnership may set a new bar for what enterprise marketing platforms must do next.

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