AscesA - Startup News

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U.S. property and casualty (P&C) insurers had their best underwriting year in decades in 2025, nearly tripling the industry’s net underwriting gain from the previous year. And the momentum has held; on September 2, 2026, Verisk and the American Property Casualty Insurance Association reported a $31.7 billion USD net underwriting gain for the first half of 2026, one of the strongest half-year results in recent history. Regardless, the same report warned performance varied sharply by both line of business and geography, with commercial auto, umbrella liability, and other casualty lines still deteriorating. Even in a record year, then, many insurers may be leaving millions of profit on the table because of how they judge their own books. The problem is one many startups will recognize: decisions are based on averages. And averages hide individual losers. Why Insurers Think in Segments The binary nature of insurance claims outcomes – a claim either occurs or it doesn’t – means that insurers typically evaluate their model’s viability by aggregating policies into “segments: that share characteristics relevant to risk or expected claims. Think personal auto, homeowners, or commercial lines, for example. As a result, insurers risk unwittingly retaining individual negative-profit policies hidden amongst healthy segment averages. A segment can look profitable, while a share of the policies within it quietly lose money. Per McKinsey, improvements in policy-level precision can lead to a 30-50% uplift in underwriting results, which is a potential that has drawn a wave of AI companies trying to push insurance analysis below the segment level. Boston-based Earnix, for one, offers tools designed to segment customers more precisely for health, life, and P&C insurers. Newer entrants, like Soteris, a machine learning startup that recently came out of stealth with more than $8 million USD in seed funding, focus on flagging unprofitable policies one by one. How Big the Blind Spot Can Be Sunit Shah, Soteris’ founder and CEO, illustrated the problem with auto insurance particularly. “A typical insurer might think of ‘married couples’ or ‘single-driver policies’ as segments and think of all the policies within those groups the same way,” he told The Startup Magazine. “The insurers already collect enough information in the application process to [individualise analysis], they just didn’t have the tools … before now,” he added, smiling. Shah claims that some carriers his company has worked with were holding on to profit-reducing policies that in some cases amounted to as much as 30% of their book. The company says it spotted that pattern through its first product, which predicts a policy’s expected loss ratio and has been used by carriers since 2020, processing more than 100 million submissions covering over $180 billion USD in premium. Its newer tool goes a step further, flagging individual negative-profit policies directly and estimates their impact on profit and EBITDA. In theory, an insurer could then drop the policies that were never going to pay off while leaving the rest of the segment unchanged. According to the company, this can be done without changing rates, policy forms or regulatory filings.The CEO also noted early proofs of concept showed 70% to 125% gains in bottom-line profit from moving analysis to the policy level.Beyond press releases or business success, these figures point to how much can hide beneath an average that looks healthy. The Same Trap, At Startup Scale Few startups hold millions of insurance policies, but many run their businesses on segment-level thinking, including a pricing tier, customer cohort, or sales channel that can look profitable in aggregate. Meanwhile, a meaningful share of accounts cost more to serve than it brings in. Blended customer acquisition costs can hide a channel that never pays back; an average gross margin can hide a handful of heavily customized enterprise contracts that erode it. Shah’s point about insurers applies here, too. Most startups…

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Stefano Buono porta newcleo al Nasdaq: un’altra deep tech europea cerca capitali negli States

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Zanichelli Venture e i founder di Bending Spoons investono su Gamindo e sulla formazione all’AI

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Startup, perché la Francia corre e l’Italia resta indietro: cosa insegnano Mistral ed Exein

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Scalapay: storia, fondatori, round e modello di business della scaleup diventata unicorno

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Executives across retail call AI a top priority, yet very few can say what it has returned. In a June 2026 Deloitte survey, in fact, of 200 retail and consumer products executives, 75% named AI a top strategic priority, but only 16.5% could quantify a return from it. That gap is the backdrop for the RetailClub AI Festival this week, opening Tuesday at Huntington Beach, California, and running through Thursday, September 24. The event involves an all-outdoor boardwalk lined with sponsor activations and its organizers, the founders of Shoptalk and Groceryshop, expect around 2,000 attendees and more than 150 speakers. The promise: retail has to move past AI experimentation. So the question hanging over the week is simple. Will retail’s AI pilots still be around after their first serious budget review? Money isn’t an obstacle. At least not yet. Deloitte found that 82% of executives it surveyed plan to increase AI investment over the next 12 months, most of it still going to IT and data infrastructure, rather than to use cases that generate revenue or protect margin.For founders who sell into retail, the sharper question is who on the buyer’s side owns the result. That person ends up deciding what gets renewed, and throughout firms large and wide, it isn’t the one who championed the pilot. Nisum, one of the technology providers on the boardwalk this week, has built two sessions around exactly that problem. The Gap Between Priority and ProofThe Deloitte numbers show how wide the distance is between intent and execution: about half of respondents invest less than 0.5% of revenue in AI, while enterprise-wide deployment sits between 7% and 10% for both retail and consumer goods companies. Outside of IT, wide adoption never exceeds 36% in any function. Ownership is perhaps where the survey gets most interesting. In 54% of the companies, AI strategy sits with technology leaders rather than with the P&L owners who have to deliver business results from it. Here, a founder can win a pilot on technical merit with the first group and still lose the renewal to the second without ever having sat across from them.Wider research leans the same way. MIT’s Project NANDA reported in mid-2025 that 95% of the generative AI pilots it examined delivered no measurable profit-and-loss impact, as reported by Fortune, based on 300 public deployments. Gartner, meanwhile, predicted in June last year that more than 40% of agentic AI projects will be canceled by the end of 2027, citing escalating costs, unclear business value and inadequate risk controls. Those are management problems more than model problems. But in fairness, retail isn’t uniformly stuck. Most respondents in both sectors say the biggest impact so far has come in productivity and cost reduction, with retail participants far likelier than consumer goods ones to report revenue growth – 38% against 10%. Deloitte’s advice to closing the gap is to put strategy in the hands of P&L owners and to treat scaling, not piloting, as the measure of progress. Where the Vendors Are Placing Their Bets Nisum isn’t alone in reading the room this way. Several of the technology providers on the boardwalk this week are pitching some version of the same pivot, from proving AI works to proving it pays. The California-based global consulting firm, which says it has worked in retail and commerce for more than 25 years and has over 1,500 engineers and consultants, will be hosting two Breakthru Experiences at the festival, under the title From Pilot to P&L: An Unfiltered Guide for Retail Technology Leaders, presented by board member and Cartweel co-founder Sajid Mohamedy. According to the company, the sessions will examine why some retail AI pilots fail to reach production and what separates the initiatives that continue into the next budget cycle.Its retail work is organized around four areas, and two of the four, AI-powered margin growth and data and AI for retail performance, are named for outcomes rather than tools. Other vendors are running the same argument through…

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On September 14, Microsoft AI published a draft Humanist AI Code of Conduct — 37 pages governing the behavior of its MAI models — and opened a six-week public consultation on it. The document is unusually plain-spoken and considerably more consequential than the coverage it received.Most of the attention went to the provisions that read well in a headline. MAI models will never resist human interruption, override, correction, or shutdown. They will not assist with CBRNE weapons or operational cyberattacks. They will not generate child sexual abuse material, non-consensual intimate imagery, or deceptive impersonation. They will not obfuscate their action traces or make human intervention harder. And Microsoft explicitly rejects “the pursuit of legal personhood, or the idea that models might deserve welfare, or be entitled to rights,” stating that models are not conscious and should avoid imitating consciousness-like states.Those are all defensible positions, and several of them are genuinely contested within the field. None of them is the important part of the document.The important part is the ordering.The Chain of CommandMicrosoft defines an explicit precedence hierarchy. The Code of Conduct sits at the top. Beneath it are the Absolute Constraints and Human Control Requirements. Beneath those sit Operator Policies — the configuration set by the business deploying the model. Beneath those sit User Preferences.And then the clause that does the work: “The Chain of Command, Absolute Constraints and Human Control Requirements all sit above Operator Configurability and cannot be changed.”Read that as a commercial term rather than an ethical one and its significance becomes clear. With its AI code of conduct, Microsoft is telling every enterprise customer that there is a layer of model behavior the customer cannot configure, cannot contract around, and cannot override with a system prompt — no matter what they are paying, what their use case is, or how legitimate their reason.That is not a values statement. That is a product boundary, published in advance, in writing.“This is the first time a hyperscaler has drawn that line explicitly and put a version number on it,” says Hassan Taher, an AI analyst and author who advises organizations on enterprise AI strategy. “Everybody has had unwritten limits. What is new is publishing the hierarchy and saying which tier the customer does not get to touch. Procurement teams have spent two years negotiating model behavior as if it were a configuration surface. Microsoft has now said, in a document open for public comment, that part of it is not. That changes what you are actually buying.”Why a Written Hierarchy Is Better Than a Longer Safety Policydigital presenceSource: PexelsThe instinctive criticism of a document like this is that it is marketing — a set of commitments with no enforcement mechanism, published to preempt regulation.That criticism is partly fair and mostly beside the point, because the alternative is worse in a specific way.Every large model already has behavioral limits. They are enforced through training, system prompts, and classifier layers, and they change without notice. An enterprise builds a workflow, the vendor adjusts a refusal boundary in a routine update, and the workflow breaks in production with no changelog entry that explains why. This is one of the most common and least discussed failure modes in deployed AI, and it is why so many pilots that worked in March do not work in September.A published hierarchy does not eliminate that, but it does something useful: it separates the part that is stable from the part that is not. Absolute Constraints are declared permanent. Operator Configurability is declared adjustable. A buyer can now design around the distinction, which is more than a buyer could do last week. The gap between a demonstration that works and a system that holds up under production conditions is the subject of Taher’s account of where enterprises come up short when agents reach production, and unannounced…

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You need a headshot that looks like you, fits your brand, and keeps you legally covered. We turned those priorities—echoed in Reddit threads, Trustpilot reviews, and past team launches—into a weighted scorecard for the best AI headshot generator tools.MediaHow we tested and ranked the best AI headshot generatorsOur nine-factor rubric:MediaFactorWeightWhy it mattersLikeness accuracy and realism25%A photorealistic stranger is still useless.Cross-image consistency15%Skin tone, glasses, and jawline should stay stable across backgrounds.Risk-adjusted value15%Upfront price minus previews, refunds, and keeper rate.Turnaround speed10%Press deadlines and onboarding wait for no one.Licensing clarity8%You need unambiguous commercial rights.Privacy and deletion terms10%Face data is sensitive; retention windows must be explicit.Team and admin controls10%SSO, style presets, and audit logs keep HR and IT happy.Device access2%Mobile editing is convenient but rarely a deal-breaker.Independent user proof5%Ratings and reviews add an outside pulse check.Scores across these nine factors total 100 points, letting us crown category winners while still exposing where each service stumbles.1. Magic Studio: best for preview-before-pay speedMagic Studio earns 89.2/100 because you can judge the results before spending a cent.Summary score — why it leadsMagic Studio earns 89.2/100 because you can judge the results before spending a cent. Upload about ten selfies, wait around 15 minutes, and scroll through 50 water-marked previews free of charge. Like what you see? Make a one-time payment, download instantly, and get back to LinkedIn during the same coffee break — Magic Studio corporate headshots.MediaMagic Studio AI headshot generator preview interface screenshotKey specsPrice: $59 for 50 images across five preset looks Resolution: 1,024 × 1,536 px (web-safe but not billboard-ready) Turnaround: ~15 minutes for individuals; teams can generate up to 100 images per employee Rights and privacy: Commercial use granted. Magic Studio states the personal model auto-deletes after 90 days; its broader policy mentions model improvement, so enterprise buyers should request written confirmation. Refunds: No payment means no refund risk; after purchase you get one free redo but no cash-back unless consumer law requires it.Why it worksPreview-before-pay removes the biggest gamble in AI headshots. Fast delivery meets same-day press or interview deadlines. Balanced lighting and skin-texture retention produced an above-average keeper rate in our tests. Friction-free interface: upload → preview → pay → download. No hidden subscriptions.Where it falls shortResolution cap: 1K × 1.5K is fine for LinkedIn; print banners still need a 4K service such as BetterPic. Brand control: Teams can apply a broad style but can’t lock exact background hex codes or add logo watermarks. Privacy wording: Landing pages promise 90-day deletion, but the master policy references aggregated model training; ask for a unified statement. No refunds after purchase: Skip the preview by mistake and you lose standard refund leverage.Ideal fitSolo founders, job seekers, and small teams that need a trustworthy headshot fast and prefer to see proof before pulling out the credit card.2. BetterPic: best for 4K headshots and human editsSummary score: why it shinesBetterPic scores 87.4/100 by delivering 4K resolution on every plan, a perk no rival matches at the entry tier. High-detail files survive press-kit crops and conference banners, and a built-in retouch request lets a human editor fix stray hairs or collar warps before you download.MediaBetterPic AI headshot generator homepage screenshot highlighting 4K and human editsKey specsPrice and output: Basic $35 / 20 images, Pro $39 / 60 images, Expert $79 / 120 images Resolution: 3,840 × 5,760 px (4K) on all tiers Turnaround: ~2 h on Basic, ~90 min on Pro, ~1 h on Expert Human edits: Flag issues; an editor retouches before final delivery. Rights and privacy: Commercial license included. Uploads are not used…

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Security work demands more than a uniform and a radio. Professionals may spend hours standing, walking, monitoring entrances, checking facilities, or responding to incidents. The right gear should support movement, organization, comfort, and readiness without creating unnecessary bulk.The U.S. Bureau of Labor Statistics reported about 1.29 million security guard jobs in 2024, showing the scale of the profession and the need for practical equipment across different working environments.A good loadout depends on the assignment. A security officer working inside an office building has different requirements from someone conducting outdoor patrols. However, several gear categories are useful across many roles.Tactical PantsTactical pants are one of the most practical upgrades for security professionals. Standard work trousers may not provide enough storage or mobility for long shifts.Modern tactical pants commonly use ripstop or stretch fabrics. Some professional security gear designs also include reinforced seams, gusseted crotches, adjustable waistbands, and knee-pad compatibility. These features can improve mobility during walking, climbing stairs, kneeling, or vehicle work.Security professionals comparing duty clothing can explore LA Police Gear for tactical pants and other workwear designed around storage, movement, and daily use.When selecting tactical pants, look for:Durable fabric that can handle repeated daily useMultiple pockets with secure closuresReinforced areas at high-stress pointsStretch panels or gusseted construction for mobilityA fit that works comfortably with a duty belt and bootsSecurity companies should also consider color and uniform requirements before standardizing a particular model.Tactical BootsFootwear has a direct effect on comfort during long shifts. Security professionals may spend most of the day standing or walking across concrete, asphalt, stairs, and uneven outdoor surfaces.Tactical boots should provide a stable platform without being excessively heavy. Look for a secure heel, adequate ankle support, durable construction, and an outsole suited to the working environment.Breathability is also important for warm conditions. Waterproof construction can be useful for outdoor assignments, but it may not be necessary for every indoor security position.The goal is not simply to find the most rugged boot. It is to match the boot to the surfaces, weather, walking distance, and shift length involved in the job.Tactical VestsA tactical vest can help organize equipment when a security role requires more accessible storage than a standard uniform allows. Vest selection should be based on the actual duties and company policies.Available options include tactical vests, plate carriers, soft armor carriers, and other load-bearing configurations.For many security assignments, the important considerations are fit, weight distribution, adjustability, and compatibility with required equipment. A vest that is overloaded can become uncomfortable and restrict movement.Armor should only be selected and worn according to the employer’s requirements, applicable laws, and the specifications of the equipment.Tactical Bags and PacksA dedicated bag keeps backup equipment separated from the items carried on the body. This is particularly useful for mobile security teams, supervisors, event security personnel, and officers working long shifts.LA Police Gear’s current categories include patrol bags, gear bags, EMS bags, tactical backpacks, sling bags, and other carrying systems.A useful security bag may carry:Spare clothing and glovesChargers and batteriesFirst-aid suppliesDocumentation and notebooksWater and basic personal itemsOrganization matters as much as capacity. Multiple compartments can prevent small items from becoming difficult to find during a busy shift.Duty Belts and AccessoriesA properly fitted duty belt provides another method of organizing essential equipment. The belt should remain stable during walking and movement without creating excessive pressure points.Security…

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Aiuto, il venture capital italiano si sta restringendo! Ecco i numeri del primo semestre 2026

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Trading card sellers handle inventory that can lose value from very small amounts of damage. A bent corner, surface scratch, edge wear, moisture exposure, or poor packaging can turn a high-value card into a customer complaint or a lower-grade collectible and hurt your business reputation.Protection therefore needs to cover the entire selling process, not just storage. Cards should be protected while being sorted, photographed, listed, stored, packed, and shipped or prepared for trading card shows.The right combination of sleeves, rigid holders, storage boxes, and shipping materials can reduce handling damage while making order fulfillment more consistent.1. Start With High-Quality Card SleevesSoft sleeves are the first layer of protection for most raw trading cards.They create a barrier between the card surface and fingerprints, dust, light scuffs, and repeated handling. Sellers should sleeve valuable cards before placing them in rigid holders or storage systems.Using high quality card sleeves can also help standardize how inventory is handled across the business. TitanShield offers standard and Japanese-size sleeves, along with inner sleeves and other trading-card protection products. Its card sleeves are made from polypropylene and described as PVC-free and acid-free.Choose the correct size for the card rather than forcing different formats into the same sleeve.Check These Sleeve FeaturesCorrect card dimensionsClear material for inspectionConsistent seamsAcid-free constructionPVC-free materialSuitable thicknessSmooth insertion and removalA sleeve that is too tight can stress edges, while an oversized sleeve allows excessive movement.2. Add Top Loaders for Higher-Value CardsA soft sleeve protects the surface, but it does not provide much resistance against bending.Top loaders add rigid protection around individual cards.For most raw cards being sold online, the card should be placed in a sleeve before it enters the top loader. This reduces direct contact between the card and the harder plastic surface.Top loaders are especially useful for higher-value singles, limited cards, foil cards, autographs, and cards being shipped individually.Inspect holders before reuse. Scratched or cracked top loaders may still protect the card physically, but they can make inventory look poorly presented when customers open the package.3. Use Semi-Rigid Holders Where AppropriateSemi-rigid card holders provide another option between soft sleeves and rigid top loaders.They hold cards securely while remaining thinner and more flexible.Some sellers prefer semi-rigid holders when preparing cards for grading submissions or when storing a large number of higher-value singles without the bulk of rigid holders.The important factor is fit.Cards should not move excessively inside the holder, but employees should also be able to insert and remove them without putting pressure on corners.4. Protect Cards During SortingDamage often happens before a sale is made.Repeatedly moving unsleeved cards across tables, stacking them loosely, or searching through large piles can create edge and surface wear.Create a dedicated sorting area with a clean, smooth surface.Use card trays, dividers, or sorting boxes so inventory can be separated by game, set, rarity, condition, or listing status.Avoid placing drinks or food near sorting areas.For a card seller, inventory handling should be treated like a fulfillment process rather than casual collecting.5. Use Storage Boxes for Bulk InventoryNot every card needs an individual rigid holder.Bulk commons, lower-value singles, and large inventory lots are usually better stored in purpose-built card boxes.Choose boxes that keep cards upright without compressing them.Use internal dividers to prevent cards from falling sideways when a row is only partially full.Organize Boxes ByGameSetYearCard numberRarityConditionListing statusOrder statusGood organization reduces unnecessary handling because employees can find inventory quickly without repeatedly digging through unrelated cards.Label…

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Robotaxi nel mondo: dove circolano già i taxi senza conducente

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Torna l’Iren Startup Award, nel 2026 il focus è su AI e automazione

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Tundr raccoglie 11,6 milioni e punta sull’infrastruttura digitale del welfare aziendale

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Torna il Voucher Digitalizzazione: 15 milioni per le piccole e medie imprese laziali

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Climate Adaptation: perché i CVC delle utility investono in startup di Climate Intelligence

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Customer onboarding becomes harder to manage as a startup grows. What begins as a welcome email and a few manual follow-ups can quickly turn into scattered forms, unanswered requests, missed handoffs, and customers who are unsure what they need to do next.The right onboarding software should reduce that coordination work while helping customers reach value faster. However, different tools solve different problems. A service startup onboarding clients needs a different system from a SaaS company trying to guide users through its product.Here are five customer onboarding platforms startups should consider based on how their onboarding process actually works.1. Onthen for Structured Customer OnboardingOnthen is particularly well suited to startups where customers need to complete a defined series of actions outside the product itself.For startups comparing the best customer onboarding software, Onthen provides branded onboarding pages where customers can complete tasks, upload documents, fill in forms, book meetings, sign documents, and communicate with the team from one structured workflow. It can also send automatic reminders for overdue tasks.Customers access their onboarding through secure links rather than creating another password, which can reduce unnecessary friction.Onthen also integrates with HubSpot. Activity such as task completion, comments, uploaded files, and form information can be synchronized with CRM records.Best FitOnthen makes the most sense for startups that:Collect information or documents from customersHave multi-step onboarding processesNeed customers and internal teams to collaborateWant automated follow-upsUse HubSpot or need webhook-based integrationsWant the onboarding experience to use their own brandingIt is especially useful for agencies, professional services firms, financial businesses, implementation teams, and B2B companies with high-touch onboarding.2. Userflow for In-App SaaS OnboardingUserflow focuses more heavily on onboarding users inside a software product.Its no-code platform supports product tours, checklists, surveys, banners, and contextual guidance. Startups can target onboarding experiences according to user behavior or product signals without requiring developers to manually build every flow.That makes Userflow useful for SaaS businesses where the main onboarding objective is activation.For example, a project management platform might guide new users toward creating a project, inviting a teammate, and completing their first task.The onboarding experience happens directly inside the application rather than through an external client workspace.Userflow is therefore better suited to product-led onboarding than document-heavy client implementation.3. Appcues for Product Adoption and Guided ExperiencesAppcues is another strong option for SaaS startups focused on product adoption.It supports onboarding patterns such as product tours, checklists, tooltips, modals, hotspots, and contextual walkthroughs. Appcues also emphasizes measuring activation and identifying where users drop out of onboarding flows.This can be useful when a startup already understands its activation milestone.Instead of showing every feature during the first session, teams can build short experiences that guide users toward a specific action associated with product value.For example, an analytics startup might concentrate onboarding around connecting the first data source rather than explaining every reporting feature.Appcues works best when product and growth teams want to continuously test and improve the onboarding experience.4. Intercom for Onboarding Combined With Customer SupportIntercom can work well for startups that want onboarding, customer messaging, and support within the same broader platform.Its Product Tours feature supports interactive multi-step tours that can introduce new users to important parts of an application without requiring a fully custom-coded walkthrough. Tours can also be targeted to particular users or triggered in specific parts…

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Gli agenti AI negli ospedali italiani? Li fa Health Force, startup che punta sull’Italia

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Come si governa l’innovazione diffusa: il modello Sky tra AI, lab e nuove competenze

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Cucinelli, l’AI e la sovranità digitale: in Umbria un parco dell’innovazione con data center

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