Generative AI Solutions
Unlock business transformation with Generative AI systems that deliver automation, intelligent reasoning, and personalized digital experiences. AiPearlz develops custom LLM-powered applications, enterprise-grade RAG (Retrieval-Augmented Generation) pipelines, AI agents, and domain-specific fine-tuned models to elevate decision-making, accelerate operations, and create competitive advantage.
Our solutions are designed with measurable performance goals, robust security, compliance, and optimized total cost of ownership.
What We Offer
- 1. Custom LLM-Powered Applications
- Develop intelligent applications using:
- OpenAI GPT-4o / GPT-4.1 / GPT-5 API
- Meta LLaMA 3 / Mistral
- Google Gemini
- Anthropic Claude
- Use cases:
- Support automation tools
- AI copilots for employees
- Custom knowledge assistants
- AI-powered documentation or learning platforms
- 2. RAG Systems (Retrieval-Augmented Generation)
- Build business-ready AI that provides accurate, up-to-date, and context-aware answers using your private data.
- Technologies we use:
- LangChain
- LlamaIndex
- Vector databases: Pinecone, Weaviate, Milvus, ChromaDB
- Embedding models (OpenAI, Cohere, Voyage)
- Deliverables:
- Document ingestion pipelines
- Chunking & vectorization
- Semantic search
- Source-grounded AI answers
- Governance layer & audit logging
- 3. AI Agents & Automation
- We build autonomous and semi-autonomous agents that can reason, plan, and perform multi-step tasks.
- Capabilities:
- Multi-tool agents (browser, databases, APIs, files)
- Task orchestration & memory
- Autonomous workflow execution
- Role-specialized teams of AI agents
- Frameworks:
- OpenAI Assistants API
- LangGraph
- CrewAI
- AutoGen
- Use cases:
- Automated research
- Financial analysis
- Lead enrichment
- Back-office operations
- Report generation
- Data extraction and processing
- 4. Model Fine-Tuning & Custom Training
- For enterprises requiring domain-specific models, we provide:
- Instruction fine-tuning
- Domain adaptation
- Dataset curation
- Safety & evaluation tuning
- Knowledge reinforcement
- Supported model families:
- GPT-fine-tune
- LLaMA 3 / Mistral
- QLoRA, LoRA, PEFT-based optimization
- 5. Multi-Channel Conversational AI
- Build advanced conversational systems powered by GenAI:
- Web chatbots
- WhatsApp Business bots
- Voice assistants (Twilio, Dialogflow, Amazon Connect)
- Enterprise helpdesk AI
- Includes:
- Conversation design
- Tool use & function calling
- User profiling
- Workflow automation & integrations
- 6. Document & Data Intelligence Systems
- Transform unstructured content into searchable, structured, and actionable intelligence.
- Capabilities:
- OCR + Vision Models (Microsoft, Google, Tesseract)
- Document classification
- Data extraction
- Automated summarization
- Legal & financial document processing
Tools & Technologies
- LLMs & Foundation Models
- OpenAI GPT series
- Meta LLaMA 3
- Mistral 8x7B / 22B
- Google Gemini
- Claude 3.x
- DeepSeek Models
- AI Frameworks
- LangChain
- LlamaIndex
- HuggingFace Transformers
- LangGraph
- CrewAI
- AutoGen Studio
- Vector Databases
- Pinecone
- Weaviate
- Milvus
- Chroma
- FAISS
- Cloud AI Ecosystems
- Azure OpenAI + Azure Cognitive Search
- AWS Bedrock
- Google Vertex AI
- Dev & Integration Stack
- Python (FastAPI, Flask)
- Node.js
- REST / GraphQL APIs
- Webhooks
- Docker / Kubernetes
- CI/CD pipelines
- Monitoring (Prometheus, Grafana, Datadog)
Business Use Cases
- Customer Experience
- AI support agents
- Self-service automation
- Personalized user engagement
- Enterprise Efficiency
- Automated knowledge answers
- AI research assistants
- Meeting/Email summary automation
- Documentation automation
- Data & Intelligence
- AI-powered dashboards
- RAG search portals
- Real-time reporting agents
- Product & Innovation
- AI copilots
- Feature generation
- Code generation assistants
- Product recommendations
Deliverables You Receive
- Full solution architecture
- Custom AI model or RAG pipeline
- Source code & documentation
- Deployment package (API, app, or agent)
- Performance analytics dashboard
- Security & governance guidelines
- 30–90 days post-launch support
Call to Action
Transform your business with GenAI systems built for performance, accuracy, and scale.
Contact AiPearlz to schedule a Generative AI strategy session.
Frequently Asked Questions
01QUESTION-01
What are Generative AI solutions?
Generative AI solutions use large language models and neural networks to produce text, insights, recommendations, code, and other content based on enterprise data and context.
02QUESTION-02
What is the difference between LLM apps and RAG?
LLM apps use a pretrained model; RAG systems connect those models to your private data via vector search, ensuring accuracy and up-to-date knowledge.
03QUESTION-03
Do you support on-premise or private deployments?
Yes. We support secure deployments using private LLMs (LLaMA/Mistral) and self-hosted vector databases.
04QUESTION-04
How long does a typical GenAI project take?
Anywhere from 3–12 weeks depending on complexity, data volume and integration requirements.