Large Language Models (LLMs) are artificial intelligence models trained with billions of text tokens to understand, generate, and translate natural language with high accuracy. They are the architecture behind tools like ChatGPT, Gemini, and others. April from ServiceNow — and represent the technical cornerstone of enterprise generative AI in 2025 and 2026.
What is a Large Language Model (LLM)?
An LLM is an AI system based on deep neural networks (deep learning), trained on large volumes of textual data—books, articles, websites, and conversations. The model learns language and context patterns, becoming capable of predicting and generating coherent sentences, answering questions, translating texts, and producing structured content.
Learning occurs in two phases: pre-training (absorption of general language patterns) and fine-tuning (Adjustment for specific tasks, such as customer service or code generation). Methods like RLHF (Reinforcement Learning from Human Feedback) make responses more aligned with expected human behavior.
How Large Language Models work
Each layer of the neural network analyzes linguistic nuances, improving contextual understanding with each iteration. The larger the volume of training data and the number of model parameters, the greater the capacity for understanding and generating data. Models such as GPT-40, Gemini, and ServiceNow's Apriel-1.5-15B operate with tens to hundreds of billions of parameters.
Comparison of the main corporate LLMs
| Model | Developer | Parameters (approx.) | Corporate focus |
|---|---|---|---|
| GPT-4o | OpenAI | ~200B | Productivity, content creation, code |
| Gemini 2.5 Pro | Google DeepMind | ~340B | Multimodal reasoning, Google Workspace integration |
| April 1.5-15B | ServiceNow | 15B | Service management (ITSM, ITAM, CMDB) — optimized for Now Platform |
Key applications of LLMs in companies
- Customer service: Chatbots and intelligent assistants with 24/7 support, reduced operating costs, and improved user experience.
- Marketing and content: Creating customized texts, emails, and campaigns at scale.
- Software development: Tools like GitHub Copilot suggest code in real time, accelerating the development cycle.
- Health and research: Analysis of clinical data, report generation, and interpretation of medical terminology.
- IT Management: ServiceNow uses LLMs in NowAssist to automate ITSM, ITAM, and CMDB workflows, reducing manual work and increasing the accuracy of operations.
How to choose an LLM for your company
Selecting a Large Language Model for corporate use involves technical and governance criteria that go beyond performance on general benchmarks:
- Data governance and privacy: On-premise or private cloud-deployed models reduce the risk of exposure of sensitive data.
- Integration with existing systems: Specialized LLMs, such as ServiceNow's Apriel, offer native integration with ITSM and ITAM workflows, eliminating layers of customization.
- Cost of inference: Larger models have a higher computational cost per call — evaluate the trade-off between accuracy and operational cost.
- Latency and availability: Critical IT applications require response SLAs below 500ms, which favors lightweight and optimized models.
- Human supervision: No LLM eliminates the need for human review in high-impact decisions — defining clear automation thresholds.
Benefits and limitations of LLMs
Key benefits: Automation of repetitive tasks, large-scale content generation, real-time analysis and insights, natural interface between humans and corporate systems.
Limitations to consider: High computational cost of training and inference, need for human supervision, risk of bias in training data, lack of genuine emotional understanding, and context limitations in simpler models.
LLMs on the ServiceNow platform
ServiceNow integrates LLMs directly into its platform through... April 1.5-15B, a proprietary model optimized for service management. Now Assist — ServiceNow's generative AI interface — uses these capabilities to summarize incidents, suggest resolutions, and automate ITSM, ITAM, and CMDB workflows without requiring complex programming.
For companies looking to implement LLMs with governance and integration into the ServiceNow ecosystem, 4MATT — ServiceNow Elite Partner in Brazil, winner of the Technology Excellence Partner Award 2024–2025, with over 80 certified specialists — offers deployment, architecture, and support for these solutions.
Why Large Language Models are a growing trend
The LLM market is growing rapidly. Gartner has identified ServiceNow as a leader in the Magic Quadrant for AI Applications in ITSM (September 2025), a direct reflection of the maturity of its language models integrated into the platform. Enterprise use of Large Language Models is expected to expand by 2030, driven by platforms such as ServiceNow, OpenAI, and Google Cloud AI.