Unlock the Future with Gen AI & Large Language Models
What We Offer
Custom LLM Integration
Integrate industry-specific models like GPT, LLaMA, Claude, Gemini, or fine-tuned open-source LLMs tailored to your enterprise needs.
Enterprise AI Co-Pilots
Deploy intelligent assistants for internal tools, customer support, R&D, and compliance using Gen AI.
AI Content Generation
Automate marketing copy, reports, blogs, emails, product descriptions, and more—at scale.
Document Intelligence
Extract, summarize, translate, and search across unstructured data—PDFs, forms, contracts—with NLP + RAG (Retrieval-Augmented Generation).
Conversational AI
Create advanced bots with multi-turn conversations, memory, persona training, and contextual understanding.
AI App Development
End-to-end Gen AI-powered app development—fine-tuned on your domain data with secure APIs.
Key Use Cases
Why SecureKloud for Gen AI?
Secure & Responsible AI
HIPAA, GDPR, SOC 2 aligned practices
LLM Customization & Fine-Tuning
On your domain-specific datasets
API Integration
Into CRMs, ERPs, and internal platforms
Cloud-Native Architecture
Runs on AWS, Azure, or your private cloud
Scalable & Measurable
ROI-centric approach to Gen AI adoption
Technology Stack & Platforms
OpenAI (GPT-4 / GPT-3.5), Anthropic (Claude), Google Gemini, Meta LLaMA
LangChain, LlamaIndex, Pinecone, Weaviate, Chroma
Vector DBs, Embeddings, RAG, Prompt Engineering, Guardrails
Kubernetes, Docker, CI/CD for LLMops
How We Engage
Frequently Asked Questions
Generative AI services use advanced models to create content, automate decisions, and generate insights across domains like document processing, customer service, and product innovation-delivering both operational efficiency and business value.
The most effective approach is to start with high-impact pilot use cases-like document summarization, intelligent search, or chat automation-followed by phased integration with existing systems through APIs or private LLM deployments.
Yes, especially with private LLMs deployed within enterprise environments. Compliance with HIPAA, GDPR, DPDPA, and SOC2 ensures responsible use of sensitive data, while RBAC and audit trails further strengthen governance.
Functions such as customer service, legal ops, marketing, finance automation, and product engineering see measurable ROI. For example, contract review automation or report generation can cut manual workload by 60-70%.
Highly customizable. Models can be fine-tuned on proprietary data or domain-specific corpora (healthcare records, financial documents, etc.) to improve accuracy, relevance, and regulatory alignment.
Foundational models (e.g., GPT, LLaMA) are pre-trained on broad datasets. Custom LLMs are refined versions tailored for specific tasks or industries-offering better performance, context retention, and reduced hallucinations.
Yes. Seamless integrations are possible via REST APIs, SDKs, or plugins. These enable generative models to interact with CRMs, ERPs, knowledge bases, and ticketing systems-without disrupting existing workflows.
ROI timelines vary by use case, but most enterprises see tangible outcomes within 6-12 weeks post-deployment-especially in automation-heavy functions. Cost savings, faster decision-making, and reduced errors are common results.