Invisible culture blogs | Invisible technologies

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Invisible culture

Inside Invisible: A culture built on ownership, growth, performance, and autonomy

Some workplaces promise comfort. Invisible offers something different: a challenge worth taking in the exciting frontier of AI technology.

Invisible culture

Inside Invisible: how our engineering team is building the future, one challenge at a time

Our Engineering team lies at the heart of our mission to revolutionize operational efficiency for clients and is driven by an insatiable curiosity and a shared determination to tackle intricate problems.

Invisible culture

Inside Invisible: how Invisible’s product team is transforming tech-enabled operations for the future

Invisible's Head of Product, Apurva Garware, has a mission: build a platform to empower organizations to redefine efficiency in a rapidly changing world.

Small language models vs. large language models

What are small language models and how do they compare to large language models? SLMs are faster, more affordable, and better for specific AI solutions.

How leading AI teams use synthetic data generation for training their models

Learn how synthetic data generation can save time and costs while improving your AI model, and discover the cost of using synthetic data without a strategy.

Supervised fine-tuning vs. RLHF: How to choose the right approach to train your LLM

Learn when to use supervised fine-tuning or RLHF to adapt LLMs for real-world use. Discover key trade-offs, use cases, and data prep best practices.

Why your LLM is misbehaving: common causes of AI failure

Invisible’s expert data strategy team reveals why many AI models fail—from flawed training data to synthetic overload—and how targeted human datasets fix these costly gaps.

AI Mullet: SLMs as the Business in the Front, LLMs as the Party in the Back

Learn how public sector agencies can employ LLMs and SLMs together to tackle complex challenges as well as every-day, mission-critical tasks.

Invisible culture

Inside Invisible: A culture built on ownership, growth, performance, and autonomy

Some workplaces promise comfort. Invisible offers something different: a challenge worth taking in the exciting frontier of AI technology.

How to build an enterprise agentic AI strategy that actually delivers ROI

Explore potential enterprise AI agent solutions and learn how leaders can build an effective and adaptable strategy for agentic AI.

3 steps to establishing better goals & success criteria for your AI projects

Explore how AI and innovation leaders can prevent these failure scenarios by establishing clear success criteria supported by data and research.

Invisible Technologies appoints McKinsey AI leader as Chief Executive Officer

Matthew Fitzpatrick to lead next phase of growth for fast-growing AI training and operations company as enterprise customer adoption scales from POC to production.

How to avoid the AI death trap and unlock real value in 2025

In 2025, it’s clear that business leaders need to reassess their approach to adopting AI from first principles. Otherwise, they risk falling into the AI Death Trap.

Invisible culture

Inside Invisible: how our engineering team is building the future, one challenge at a time

Our Engineering team lies at the heart of our mission to revolutionize operational efficiency for clients and is driven by an insatiable curiosity and a shared determination to tackle intricate problems.

The ultimate guide to enterprise AI model evaluation

Unlock the secrets to successful enterprise AI deployment with a holistic model evaluation strategy that goes beyond metrics—boost performance, safety, and user adoption.

5 ways to use AI for sales

Discover how AI is transforming sales by automating repetitive tasks, boosting productivity, and helping reps focus on what really matters—closing deals.

How to use AI for financial analysis to transform decision-making in the modern enterprise

Explore how AI for financial analysis streamlines workflows, enhances forecasting, and drives smarter decisions with the right data foundation.

Beyond vibe coding: How to use AI for software development

From intelligent code generation to workflow automation, learn how to implement AI for developers and dev teams.

How to effectively use AI for data analytics

Discover how AI for data analytics can help businesses automate manual tasks and unlock deep insights if the right foundations are in place.

How to use AI for process automation in your business

Learn how to use AI to streamline workflows, boost efficiency, and automate business processes effectively.

What to do when human data doesn’t improve model performance

Discover why more data doesn’t always improve AI models and how rich, complex human input can break performance plateaus for better real-world results.

Quality GenAI data demands human creativity—here's how Invisible harnesses it

Discover how we build high-performing creative data teams by prioritizing passion, collaboration, and culture—driving better AI training outcomes.

What is data curation and why does it matter when training AI?

Strategic data curation, not just volume, boosts AI accuracy by selecting high-quality, relevant data—key for reducing bias and improving real-world performance.

How to teach chain of thought reasoning to your LLM

Learn how to train your LLM to use chain of thought reasoning for better accuracy, logical thinking, and performance on complex tasks.

Why third party model evaluations are key for AI success in regulated industries

Discover how Invisible’s custom AI model evaluations uncover hidden risks, prevent costly errors, and ensure reliable, compliant AI—especially crucial for high-stakes industries.

We asked 5 LLMs to build us a winning March Madness bracket — here’s what we learned

We challenged top language models to create NCAA brackets, revealing key lessons on AI usability, safety guardrails, creativity, and why style guides matter for clear, useful outputs.

Small language models vs. large language models

What are small language models and how do they compare to large language models? SLMs are faster, more affordable, and better for specific AI solutions.

Invisible culture

Inside Invisible: A culture built on ownership, growth, performance, and autonomy

Some workplaces promise comfort. Invisible offers something different: a challenge worth taking in the exciting frontier of AI technology.

Invisible culture

Inside Invisible: how our engineering team is building the future, one challenge at a time

Our Engineering team lies at the heart of our mission to revolutionize operational efficiency for clients and is driven by an insatiable curiosity and a shared determination to tackle intricate problems.

Invisible culture

Inside Invisible: how Invisible’s product team is transforming tech-enabled operations for the future

Invisible's Head of Product, Apurva Garware, has a mission: build a platform to empower organizations to redefine efficiency in a rapidly changing world.

The top 3 recruiting challenges multi-unit retailers face—and how to tackle them

Struggling to hire fast and well in retail? Learn how AI and smarter processes help multi-unit retailers boost speed, quality, and consistency—without tradeoffs.

Product feed optimization: the key to improving search engine discoverability for retailers

Struggling with product discoverability? Learn how optimizing your product feed with AI and human QA can boost visibility, search ranking, and sales.

How to optimize your restaurant chain in the age of AI

Through careful implementation of AI, food and beverage-based businesses can substantially improve their bottom line and achieve greater profitability.

How AI will continue to transform logistics

Logistics firms should take a cue from Amazon and DoorDash—AI is transforming everything from product recommendations to last-mile delivery.

How to unlock AI's potential in high growth marketplaces

AI has the power to transform digital platforms, allowing them to scale more efficiently than ever before, but unlocking AI's potential is impossible without humans in the loop.

How AI can help marketplaces innovate and scale fast

Digital marketplaces face constant change—shifting consumer trends, disruptive tech, and fast-moving rivals make adaptability key to survival.

Can AI help save America’s healthcare crisis?

The U.S. healthcare system faces a labor crisis—burnout is rising, and care is slipping. AI could be the force multiplier that helps reverse the trend.

How big data and AI will combine to transform healthcare

Data fuels the AI revolution—and in healthcare, untapped data means massive potential for disruption, says Invisible’s GM of Healthcare, Rishi Madhok MD.

Financial services

How to unlock the hidden knowledge in your enterprise

RAG helps enterprises unlock hidden knowledge from unstructured data—speeding decisions, breaking silos, and transforming due diligence workflows.

Financial services

How AI will turn the back office into a strategic driver for FinServ

When people think of AI, they imagine a distant future. But in financial services, its real (and transformative) impact is already unfolding.

Financial services

Why most financial services businesses won’t maximize AI without outside help

Financial services are embracing AI but struggle without strategy and infrastructure. Discover how FinServ can become truly AI-first and thrive in a fast-changing landscape.