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NewFangled Private GenAI: The End of LLM Dependency for Enterprises
Enterprises jumped into the GenAI wave with public Large Language Models (LLMs), enthused by its ability to generate content, code, and insights. But the worries have grown along with adoption. CEOs, CIOs, and CTOs are beginning to acknowledge a harsh reality: enterprise GenAI differs from general GenAI. This is where NewFangled Private GenAI enters the picture, offering each business its own AI “brain” rather than renting one from the internet.
Enterprise governance, compliance, and domain-specific correctness were never considered when designing public LLMs. They make decisions about your company while sitting in someone else’s cloud, having been trained on someone else’s data. For mission-critical intelligence, that is not a viable model.
The Problem: Dependency on Public LLMs Is Unsustainable
Data Leaves the Enterprise
In most public LLM setups, prompts, context, and sometimes even sensitive metadata leave the organization and travel to a cloud LLM for processing. Even with encryption and contractual assurances, this creates serious questions:
- Where exactly is the data processed?
- Who has technical access to it?
- How is it logged, cached, or stored?
- Can it ever be fully deleted?
For regulated industries, this alone is enough to trigger red flags around compliance, data residency, and auditability.
Built on the Open Internet: Bias, Hallucinations, and Misinformation
Public LLMs are typically trained on massive swathes of internet data: websites, forums, social media, user-generated content, and more. That data is:
- Biased
- Noisy
- Incomplete or sometimes outright false
As a result, these models:
- Hallucinate answers that sound confident but are factually wrong.
- Inherit cultural, social, and political biases from their training sources.
- Struggle to distinguish between authoritative sources and low-quality content.
For consumers, this might be acceptable. For enterprises making decisions about risk, finance, patients, customers, or infrastructure, it is not.
The Black Box Problem
Public LLMs not only function outside of your infrastructure, but they also think outside of your control. They make decisions in a very opaque manner. You have no means to see how they came up with a response, no way to examine the intermediate thinking, and no trustworthy way to find out why a particular proposal was made.
This lack of transparency is a significant governance concern for highly regulated businesses. Regulators, boards, and auditors increasingly want explainable, traceable AI behaviour rather than results from an unpredictable black box.
Lack of Enterprise Context
General LLMs don’t understand your:
- Industry-specific terminology
- Internal processes
- Regulatory nuance
- Proprietary metrics and KPIs
They are unaware of your industry-specific jargon, internal procedures, legal constraints, and proprietary measures or KPIs. Because of this, they often interpret queries incorrectly, apply the wrong filters or time periods, and provide dashboards that are not very useful. In order to maintain useful outputs, IT teams are forced to intervene and continuously prepare data and fix logic.
These errors and discrepancies gradually undermine the organization’s trust in AI, transforming what ought to be a tactical benefit into a cause of annoyance.
Why Enterprises Need Private GenAI
The answer is not to abandon AI. It’s to change where and how intelligence happens.
- Data Sovereignty and Safety by Design
- For enterprises, the safest and most sustainable model is straightforward
- Intelligence should live where the data lives.
A private GenAI setup keeps all processing inside your infrastructure on premises or in your private cloud. Nothing leaves your control. This aligns with modern governance frameworks, internal security controls, and regulatory expectations
Building a Private, Industry-Specific Knowledge Bank
This is where NewFangled Private GenAI fundamentally changes the game. Instead of relying on the public internet as a noisy teacher, you create your own private knowledge bank, built from:
- Internal documents
- Process manuals
- Playbooks and runbooks
- Historical reports and performance data
- Expert-written guidance and domain rules
This knowledge base is:
- Fully private
- Curated and validated by your internal experts
- Tailored to your industry, your market, and your terminology
You’re no longer asking a general AI, “What do you think?”
You’re asking your own organization’s brain, “What do we know, and what should we do?”
Custom Intelligence for Each User, Role, and Department
With NewFangled Private GenAI, intelligence is never one-size-fits-all. It adjusts to the requirements of every position and function inside the company. Financial predictions, risk, and profitability are the main topics of information provided to CFOs and finance departments. Sales executives and CMOs see intelligence in relation to consumer behaviour, marketing, and funnels. Leaders in operations and supply chains receive analysis that focusses on cost, uptime, and efficiency. Guidance based on policy, regulatory requirements, and risk controls is provided to legal and compliance departments.
The enterprise’s basic knowledge base is still shared, but each job, team, business unit, or region can have its own interpretation, prioritisation, and delivery of insights. Because generic public LLMs lack the context and flexibility needed to fit enterprise-specific objectives, it is nearly difficult to achieve this degree of accuracy and personalisation.
Introducing NewFangled Private GenAI (VADY)
VADY-powered NewFangled Private GenAI is designed especially for businesses who wish to entirely own their intelligence layer and stop depending on public LLMs. The design of NewFangled functions fully within your infrastructure, whether it is on-premises or in your private cloud, in contrast to cloud-based GenAI products that rely on external APIs and third-party models. There are no public endpoints, no outgoing LLM calls, and no data fine-tuning or background training. Since every insight is produced internally, CISOs, CIOs, and compliance teams have had the degree of control and autonomy they have desired from GenAI since its inception.
Built for Private, Secure Enterprise Intelligence
With NewFangled Private GenAI:
- All computation happens inside your environment
- No data is sent to external LLMs or cloud AI providers
- No third party ever trains or tunes on your proprietary data
- Security, privacy, and governance remain entirely under enterprise control
This architecture ensures that the intelligence layer becomes a core enterprise asset—not something you rent from a cloud vendor.
Architected for Decision Intelligence, Not Just Text Generation
VADY goes far beyond general-purpose language models. It is built as a decision intelligence engine capable of handling complex analytical tasks such as:
- Multi-level revenue and margin analysis
- Ratio-based comparisons (e.g., revenue vs. discount trends)
- Year-over-year and quarter-over-quarter performance review
- Time-series pattern detection and anomaly discovery
- Granular slicing across products, segments, geographies, and regions
NewFangled Private GenAI provides accurate, contextual insights in line with organisational logic rather than generic or superficial summaries. It acts like a real analytical partner, one that is aware of how your company operates.
Zero Developer Dependency for Business Logic
Traditional AI copilots still require technical teams to build semantic models, define joins, or maintain complex formula layers. NewFangled eliminates this dependency entirely.
Business users can define their logic through:
- Natural language instructions
- Guided configurations
- Domain-specific prompts tailored to their workflows
Learning DAX, SQL, semantic modelling, or “prompt engineering” tricks is not necessary. Although they are still in charge of system integration and access control, IT teams are no longer a barrier for all analytical queries. Intelligence becomes business-owned, adaptable, and scalable.
Industry Use Cases: Why Private GenAI Matters Everywhere
Banking & Finance
Accurate, compliant, and fully explicable intelligence is required by the financial industry. By analysing sensitive financial data completely within the institution’s own environment, NewFangled Private GenAI satisfies these standards. This guarantees that every insight is auditable and safe.
Among the essential Features are:
- Risk modelling based on past transactional behaviour
- Finding fraud patterns without disclosing client information to other parties
- Regulatory analytics with clear, understandable suggestions
Financial organisations may now confidently employ GenAI to make crucial choices without sacrificing security or compliance.
Healthcare
Healthcare organisations are unable to transfer PHI to outside LLMs because to stringent privacy requirements. Clinical intelligence is completely safeguarded with NewFangled Private GenAI because all processing takes place locally.
Among the essential Features are:
- Patient travel and clinical route analysis within your private network are important features.
- Internal medical guidelines-aligned treatment pattern insights
- AI-assisted suggestions that adhere to local health laws or HIPAA requirements
This enables healthcare professionals to appropriately use AI without jeopardising patient confidence or breaking the law.
Telecom
Telecom companies manage vast amounts of proprietary network and customer behavior data. So, NewFangled Private GenAI helps operators turn this information into actionable intelligence while keeping all data in-house.
Key capabilities include:
- Churn prediction based on proprietary usage models
- Network performance diagnostics that never leave the NOC
- Geo-specific pattern detection for expansion, optimization, and rollout planning
This empowers telecom operators to improve service reliability and customer retention with complete data security.
Retail & E-Commerce
Retail and e-commerce businesses rely on precise insights to improve forecasting, pricing, and customer experience. NewFangled Private GenAI transforms internal operational and customer data into highly contextual intelligence.
Key capabilities include:
- Demand forecasting using real sales, supply, and logistics data
- Dynamic pricing optimization tailored to margin and inventory goals
- Customer segmentation grounded in CRM data not generic web behavior
This leads to smarter merchandising decisions and more personalized customer engagement. NewFangled Private GenAI ensures that intelligence is obtained from reliable internal sources rather than the public internet by operating on a private, expert-curated knowledge bank across all sectors. This ensures enterprise-grade control, accuracy, and privacy at every stage.
Conclusion: The Era of LLM Dependency Is Ending
General GenAI was a valuable starting point; however, it was never designed to serve as a long-term solution for enterprises. As a result, organisations relying on public LLMs face several significant risks, including strong vendor lock-in, limited oversight, unpredictable behaviour, and biased or hallucinated outputs. Moreover, these models operate outside the enterprise environment, which further increases security and governance concerns. Consequently, most organisations can no longer afford to ignore the vulnerabilities that arise when mission-critical decisions depend on externally controlled GenAI systems.
A completely new approach is provided by NewFangled Private GenAI. It guarantees that sensitive data never escapes organisational borders by keeping intelligence entirely within your infrastructure. Businesses may create their own expertly curated knowledge banks based on internal best practices and industry context. Decision intelligence may be tailored to each function, department, and geographic area, ensuring that it accurately reflects how the company really runs.
This shifts AI from a rented, external service into a strategic enterprise asset the organization truly owns. So the real question is no longer “Should we use GenAI?”. The question is “Who owns our intelligence—our organization or an external LLM provider?”
With NewFangled Private GenAI, the answer is finally clear:
“your enterprise owns the intelligence, the knowledge, and the future.”
Sahana Hanji is a data analyst with an understanding of business management and a strong foundation in data analysis, business intelligence, and machine learning. She has hands-on experience working with AI startups and fintech companies in both the UK and India. She has built dynamic dashboards, led predictive analytics projects, and delivered data-driven insights to improve business outcomes.