Invisible Technologies

Your AI project has an 85% chance of failure. The statistic isn't meant to discourage you. It's meant to prepare you. We've identified the critical patterns that lead organizations into what we call the "AI Death Trap": When businesses mistake AI's long-term potential for short-term magic, only to watch their investments stall at the pilot phase. Based on our work with both frontier AI model developers and enterprise implementers, here's what's really happening: - The "software mindset" approach fails with AI - Getting to 80% is deceptively easy, but that final 20% is where most initiatives collapse - Adoption of plug-and-play solutions that lack scalability and customization The solution isn't throwing more resources at the problem. It requires changing your approach through purpose-built models tailored to specific use cases, systematic human oversight at critical decision points, flexible infrastructure supporting multiple specialized models, and commitment to continuous learning. So why do most AI pilots never reach production? There are five root causes we consistently observe, illustrated in the image below. #AIStrategy #EnterpriseAI #BusinessTransformation

AI adoption is facing a paradox: billions have been invested in AI capabilities that fail to deliver business outcomes. The culprit? Not technology limitations, but data quality. While everyone chases massive datasets, the truly competitive edge now comes from targeted supervised fine-tuning (SFT) datasets. It's no longer about how much data you have, but how effectively you refine your models with specialized, high-quality data. The results speak for themselves: - Enhanced domain-specific performance - Significantly lower compute costs - Improved model reasoning across complex tasks The winners in the AI race won't be those with access to the most data, but organizations that can seamlessly blend human expertise with technological capability to create carefully curated datasets that solve real business problems. What's your experience with fine-tuning? Has your organization moved beyond the volume game to quality-focused approaches? #Invisible #SFT #EnterpriseAI #DigitalTransformation #AIStrategy

While you're testing chatbots, your competitors are deploying autonomous AI teams that transform operations across departments. But how does Agentic AI actually work? They're not 'set and forget' systems. Every action follows a cycle, as seen in the image below. Take retailers and manufacturers, for example, struggling to balance their inventory needs with supply chain availability. Their data can be stored in multiple databases, and reporting can be difficult to synthesize. An AI agent can integrate with these databases; extract relevant data; send communications to ensure shipments and deliveries, all with minimal oversight from human workers. But Agentic AI projects can easily become a drain on budgets if they’re not carefully planned. Make sure you: - Start with a use case to ensure it delivers ROI. - Research the end user to secure adoption. - Source high-quality training data. #AgenticAI #EnterpriseAI #DigitalTransformation #AIStrategy

Everyone's talking about making AI more efficient, but the reality is companies are struggling to make it work. 78% of companies have built GenAI prototypes despite more than half lacking internal expertise in data preparation, according to our recent study of 500+ tech leaders. While companies race to deploy AI, they're hitting the same walls: - Unsustainable costs with large models - Data quality issues blocking innovation - Knowledge gaps in fine-tuning techniques There's a shift happening. Companies like Boosted.ai are proving you can cut AI costs by 90% while improving accuracy—by thinking smaller, not bigger. #AI #SmallLanguageModels #AIStrategy #EnterpriseAI #Innovation

At Invisible, we’re rewriting the rules of work in the AI era. This isn’t about punching a clock—it’s about pushing the boundaries of what’s possible. We’re building the future, not following a blueprint. Join us, and experience unrivaled growth. Rise to the challenge. Transform the world. Invisible: Where limits don’t exist. Learn more: https://bit.ly/4aW0XCA #InsideInvisible #RemoteWork #AI #FutureofWork

‘Open minded and a willingness to try new things’ are what tech companies, large and small alike, are looking for in AI talent. Ben Sherry at Inc. Magazine asked execs at Accenture, Google, Zoom, and ourselves, what they’re looking for. Matthew Fitzpatrick told them, when hiring experts to help model builders and the enterprise train and fine tune their AI models: "We have a large network of subject matter experts, but still need to ensure they can work in our system. Our screening process can involve everything from multiple rounds of testing to rapid-fire interviews. Even after we onboard a new data trainer, we require them to obtain certain certifications before they can complete some tasks. The entire process is designed so that if a client needs to surge up certain skills overnight, we can meet that demand very quickly. But overall, the main thing we look for is people who are intellectually curious. People seeking to learn new things in a fast-moving environment are going to become very good over time.”

In Forbes Daily Cover Story, Francis Pedraza shares how Invisible’s inside track on AI training is going to help us automate enterprise tasks faster than traditional consultancies–expertise we acquired tackling hallucinations for OpenAI, Amazon, Microsoft, and Cohere. “We could not be more different”–referencing our employee ownership model, limited VC backing, globally remote workforce and valuation–’modest for a service company, but shockingly low for an AI firm’, as per Iain Martin’s piece. Historically, VCs took little interest because ‘services businesses have low margins and don’t scale’. This spawned our contrarian, capital-efficient model with debt-backed buybacks, investment in R&D, and profitability. SaaS has been the dominant business model from 1999-2024. But we’re about to see AI disrupt SaaS with a "services-to-software" model. AI process platforms are the future. Watch this space ??

Ever wondered what it feels like to be at the epicenter of global AI transformation? Now’s your chance. We’re hiring operations managers and directors who are strategic architects and can turn complex business challenges into breakthrough solutions. Working alongside 80% of the world’s AI leaders isn’t just a job. It’s a mission. Imagine leading remote teams that span continents, driving innovation across business units, and having genuine ownership of your impact. No bureaucratic constraints. No playing it safe. This is where ambitious operators turn potential into paradigm-shifting reality.We offer more than a role—we provide a launchpad for professionals who want to architect the future, not just manage it. Ready to redefine operational excellence in the AI era? Join us: https://bit.ly/4hLm1hv

?? Mathematics PhDs & Masters: Train the Next Generation of AI. LLMs are only as intelligent as the rules they know and the data they're trained on. We're the team that creates the data to train them on mathematics and logical reasoning. We need experts with academic, math-intensive backgrounds to write problems, grade answers, and determine assessment criteria. If you want to work on AI challenges on a flexible basis, from anywhere in the world, check it out! https://lnkd.in/drbpmhJa #InsideInvisible

We're helping enterprises cut AI training costs by 90% while improving accuracy. Drop by Booth 15 at OPEX Week: Business Transformation World Summit if you want to know how to: - Get AI projects out of pilot purgatory - Scale operations without sacrificing quality - Turn transformation plans into reality Caspar Eliot Korina Skhinas Barbara Baüer Frank Suljic #OpexWeek2025 #EnterpriseAI #OperationalExcellence #AITransformation