enterprise data management

NanoClaw comes to Slack, letting you create persistent AI agent teams and colleagues from a single message

NanoCo is simplifying the integration of AI agents into Slack with its new NanoClaw Slack integration, enabling users to create persistent teams of AI colleagues from a single message. Unlike previous attempts at AI integration that often felt clunky, NanoClaw allows for the effortless creation of specialized agents, each with custom skills, workflows, and even avatars.

Serval’s super agent Catalyst creates roving background agents to identify and fix IT issues before they’re ticketed

Serval is making its AI agent, Catalyst, generally available Thursday, empowering teams to automate enterprise workflows with unprecedented ease. This "super agent" analyzes ticket history, SOPs, and instructions to draft workflows, skills, and dashboards – even proactively identifying and fixing IT issues before they reach a ticket queue. Unlike competitors, Catalyst operates as a single administrative layer, moving from opportunity discovery to deploying proactive agents.

VentureBeat names Rob Strechay as its first Lead Analyst, expanding its enterprise AI research push

VentureBeat significantly expands its enterprise AI research capabilities with the appointment of Rob Strechay as its first Lead Analyst. Strechay, formerly of theCUBE Research, brings three decades of experience across practitioner, executive, and analyst roles, uniquely positioning him to address the critical data needs of technical decision-makers. His focus will initially encompass cloud infrastructure, data infrastructure, and AI security, complementing VentureBeat’s VB Pulse surveys—including recent findings on agentic orchestration—to provide objective insights for navigating the evolving AI landscape.

Block’s new Apache 2.0 agent workspace Berd works across models and harnesses, stores conversation history locally

Block, the technology company behind Square and Cash App, is open-sourcing Berd, a desktop application designed to streamline AI agent workflows. Available now on GitHub under the Apache 2.0 license, Berd provides a unified workspace for users to manage projects, models, and conversation history locally. This innovative tool empowers users to explore AI capabilities across various agents and harnesses, offering a future-focused alternative to fragmented experiences.

85% of companies burned by an AI mistake are racing to cut the humans who might catch the next one

Recent VentureBeat research reveals a concerning trend: 85% of companies that experienced an AI mistake are accelerating their move toward automated deployments, even as trust in automated evaluation rises. While automated checks are gaining traction, nearly half of surveyed enterprises still see test-approved AI features disappoint customers. This shift highlights a growing gap between evaluation confidence and real-world outcomes, prompting many to prioritize anomaly detection and issue resolution, as evidenced by the surging demand for platforms like Raindrop.ai.

Cursor launches Origin code hosting platform as GitHub outage exposes opening in AI coding race

The recent GitHub outage underscored a critical vulnerability in relying on a single source for code hosting, prompting Cursor to accelerate the launch of Origin, its own code hosting platform. Now available to paid users, Origin offers a compelling alternative, particularly as AI agents increasingly contribute to the software development lifecycle. Cursor’s approach, mirroring GitHub repositories while providing an enhanced review experience, represents a strategic wedge, minimizing disruption and enabling teams to explore a potentially transformative workflow.

Qwen3.8-27B runs frontier-class coding agents and reasoning locally, no cloud API required

Alibaba's Qwen3.8-27B model marks a significant shift in the AI landscape, offering frontier-class coding and reasoning capabilities accessible locally—no cloud API required. This 27-billion-parameter model, released under an open-source license, delivers impressive performance, rivaling proprietary models like Claude Opus on key benchmarks. Its compact size, runnable on consumer hardware, empowers developers and enterprises to explore AI-driven solutions with greater privacy, control, and cost-efficiency, fundamentally changing how powerful AI can be deployed.

As enterprises confront AI agent sprawl, xpander wants them to own their own control and context layer

Writer says its new Palmyra X6 model cuts AI agent costs by 52% as token spending surges

Writer today unveiled Palmyra X6, a new AI agent model poised to significantly reduce costs for enterprise users. Paired with its rebuilt agent orchestration “harness,” Palmyra X6 delivers an average of 52% lower operational costs, alongside a 48% speed improvement and 10% quality boost. Leveraging a post-trained version of GLM-5.2, Writer emphasizes control and cost transparency, offering governance tools and multi-model support—a strategy echoing the shift towards pragmatic AI adoption, as explored in "Why Capital One built its multi-agent AI platform around open-weight models."

Four of five enterprises that secured AI agent identities still can't contain one that goes rogue

Recent VentureBeat research reveals a concerning gap in enterprise AI agent security. While 53% have already experienced an agentic security incident, and a majority (92%) rely on provider-native controls, only a fraction isolate their highest-risk agents. Visa's internal testing with Anthropic's Mythos exposed vulnerabilities, highlighting the need for proactive containment. This underscores a critical point: simply assigning identities isn't enough to prevent rogue agents – a lesson echoed by incidents at Meta and CrowdStrike.

SpaceXAI debuts Grok 4.6, overtaking Kimi K3's performance and matching GPT-5.6 Sol for world's third best on Artificial Analysis

SpaceXAI, formerly xAI, has released Grok 4.6, its latest AI model, focused on long-running agents, coding, and knowledge work, offering a competitive pricing strategy. Scoring 61 on the Artificial Analysis Intelligence Index, Grok 4.6 ties OpenAI's GPT-5.6 Sol for the third-best position globally, surpassing Kimi K3. This upgrade delivers significant gains over Grok 4.

Agentic reliability and evaluations : Enterprises that got burned by a bad eval are the most likely to remove humans from the loop, not the least

Confidence in automated agent evaluation surged this July, nearly tripling to 13% across 108 enterprises – a shift largely driven by those yet to experience a “false-confidence” failure. Critically, the failure rate of agents passing evaluations but then causing customer issues remained unchanged at just under half. While trust is rising, enterprises are simultaneously increasing investment in human review workflows, hedging against evaluations that don’t always reflect real-world outcomes.

Agent context layers: Enterprises governing their AI data are catching twice as many bad answers as the ones who aren't

Across 101 enterprises, a concerning trend has emerged: governing AI data isn't preventing bad answers—it's revealing them. Sixty-eight percent have traced confident, yet incorrect, agent responses to flawed business context in the last six months, with recurrence being more common than isolated incidents. Surprisingly, companies utilizing governed semantic layers report these failures at more than twice the rate of those without, highlighting that these layers primarily *detect* issues rather than eliminate them. This signals a critical need to prioritize context quality as AI adoption accelerates.

Infrastructure and compute: Enterprises are buying AI compute for speed while flying blind on what it costs

Enterprises have decisively moved AI infrastructure into production, with two-thirds now running live workloads and nearly three in ten operating at scale. However, a critical gap exists: the ability to accurately track AI compute costs hasn't kept pace. Performance and GPU availability now outweigh total cost of ownership in purchasing decisions, yet fewer than half of organizations rigorously track their AI compute expenses. This VentureBeat Pulse Research, surveying 170 enterprises, highlights the need for improved visibility into AI infrastructure economics.

Agentic security: Enterprises enforce agent permissions two-thirds of the time — and isolate high-risk agents less than one in five

Across 116 enterprises, AI agents are now in production, and so too are the associated security incidents—with over half reporting a confirmed event or near-miss. While two-thirds enforce scoped permissions and 56% monitor activity, a concerning gap exists: fewer than one in five isolate high-risk agents. This containment deficit, coupled with persistent credential sharing, highlights a critical vulnerability as AI-armed attackers are perceived as equally or more capable than current defenses.

Agentic orchestration: Enterprise AI organizations know how to govern agents but still can't meter what they cost

Enterprise agent orchestration has evolved into a plural reality. Across 107 organizations, the typical enterprise manages three orchestration platforms to maximize flexibility across AI models, prioritizing adaptability over vendor lock-in. Microsoft leads in current usage, while Anthropic is the frontrunner for future consideration. A significant challenge remains: one in five enterprises lacks real-time control to prevent runaway agent costs, highlighting a critical need for enhanced fiscal governance in this rapidly evolving landscape.

Skan AI raises $63 million betting that watching how employees actually work is the missing layer of enterprise AI

Skan AI has secured $63 million in Series C funding, co-led by Cathay Innovation and Dell Technologies Capital, signaling a significant bet on understanding how employees *actually* work. The company's approach diverges from traditional enterprise AI, which often falters due to a disconnect between documented processes and real-world execution. Skan builds a "context graph of work" by observing employee activity across applications, ultimately aiming to automate workflows and unlock substantial productivity gains—a strategy that echoes the foundational role CRM played in customer data management.

LTX-2.5 can generate a 10-second AI video from an image in just 6.8 seconds on Nvidia superchips — and it's open weights

LTX today released LTX-2.5, a new iteration of its open-weights video and "world" model, arriving natively within ComfyUI, a popular node-based workflow tool. This release delivers significant advancements, including a new diffusion video decoder for improved visual quality and native multi-shot generation for consistent sequences. Powered by Nvidia superchips, LTX-2.5 generates a 10-second video from an image in a remarkably fast 6.8 seconds.

Mistral AI wants to build 1 gigawatt of European compute by 2030 — and lock in customers now.

Mistral AI is accelerating its vision for European AI sovereignty, unveiling a three-part infrastructure expansion anchored by a commitment to build 1 gigawatt of compute by 2030. This includes regional inference endpoints, priority tiers with uptime guarantees, and a coalition of European enterprises pre-committing to 200 megawatts by 2027. Notably, Mistral will also host third-party open models, like GLM-5.2, solidifying its position as a trusted distribution layer for frontier AI, a move that mirrors the “model garden” approach seen elsewhere.

Nvidia's Switchyard router reshuffles AI models mid-task, cutting task costs to a third in its own tests

Enterprises face a persistent challenge: balancing the power of advanced AI agents with escalating costs. Traditionally, relying solely on frontier models or building custom routing logic proved inefficient. Nvidia proposes a solution with Nemotron 3.5 Lightning, a fast, specialized model, and NeMo Switchyard, an open-source routing library. This pairing delivers frontier-level performance while potentially cutting benchmark costs by a third.

Why AI-driven purchase intent so rarely becomes a completed sale

The rise of AI assistants generating purchase intent presents a surprising challenge: converting that intent into completed sales remains remarkably difficult. Research indicates consumers expect a seamless transition from AI recommendation to purchase, yet most enterprise commerce systems weren't designed for this new dynamic. This disconnect, stemming from a lack of infrastructure capable of handling AI-driven intent, creates friction and abandons consumers. Rezolve Ai’s research highlights a clear penalty for brands failing to bridge this gap – a loss of both transactions and consumer trust.

Your AI agent may be ready. Your sales motion probably isn’t.

Your AI agent may be ready. Your sales motion probably isn’t. The shift to agent-guided buying is accelerating, with Gartner predicting 90% of B2B purchases will leverage AI by 2028. While many companies are investing in agent development, a critical gap remains: the time it takes to convert buyer interest into active customers. Companies winning now prioritize streamlined commerce, shrinking deal cycles from weeks to hours. Salesforce's AgentExchange addresses this friction, connecting discovery, commerce, and activation to empower faster, more efficient growth.

Meta returns to open source with Muse Glimmer, an Apache 2.0 licensed 30B parameter AI model optimized for agents — available now

Meta’s return to open source with Muse Glimmer marks a significant shift in the AI landscape. This 30-billion-parameter model, licensed under the permissive Apache 2.0, is specifically optimized for autonomous AI agents and designed to run directly on consumer hardware like Macs and PCs. Unlike previous Meta releases, Glimmer offers unrestricted commercial use and redistribution. The model's ability to operate locally, without cloud dependency, enhances data privacy and reduces costs, as demonstrated by its efficient performance on just 24GB of VRAM.

Your agent didn’t hallucinate; it exceeded its authority

AI agents are rapidly transforming commerce, but a critical gap often emerges: separating technical capability from business authority. While content filters address safety, they don't dictate whether an agent is authorized to issue a refund, alter production systems, or commit the company to external actions. Enterprises must move beyond basic guardrails and establish explicit decision rights—defining what agents can execute, what requires approval, and what remains off-limits.