LLM Research & Prototyping
Architecture Optimization
Improving transformer models, parameter scaling, and token efficiency.
Pretraining Strategies
Curating and preparing high-quality datasets for foundational model training.
Alignment & Safety
Ensuring outputs are safe, accurate, and aligned with user intent.
Evaluation Metrics
Testing for factuality, coherence, relevance, and performance across tasks.
Efficiency Research
Reducing compute cost using quantization, distillation, and low-rank adaptation (LoRA).
Multimodal & Instruction-Tuning (New Dimension)
- Expands LLM capabilities to handle text, image, video, audio, and even sensor data through multimodal training.
- Incorporates instruction-tuning and chat-based fine-tuning to align responses with natural conversational formats, as seen in models like GPT‑4o and Gemini.
- Custom LLMs trained on your private data
- Chatbots and copilots tailored to internal knowledge bases
- RAG (Retrieval-Augmented Generation) systems for high-accuracy responses
- MVPs of AI products built with open-source or API-based LLMs
- Performance benchmarks for different model types (GPT-4 vs. Claude vs. LLaMA)
Why It Matters
Investing in LLM research and prototyping enables enterprises to:
- Validate LLM capabilities before full-scale deployment
- Reduce development risk through experimentation
- Build differentiated, domain-aware AI products
- Stay ahead in the fast-evolving GenAI ecosystem
1. Rapid Innovation and Proof of Concept
Quickly test your ideas using pre-trained models and custom LLM workflows. Build MVPs (Minimum Viable Products) in weeks, not months.
2. Domain-Specific Customization
Tailor LLMs to your industry or internal knowledge base, resulting in higher accuracy, better relevance, and more actionable outputs.
3. Competitive Differentiation
Develop proprietary AI capabilities that are uniquely aligned with your data, workflows, and strategic goals—hard to replicate by competitors.
4. Reduced AI Adoption Risk
Evaluate model safety, performance, and bias in a controlled, low-risk environment before investing in large-scale deployment.
5. Scalable Architecture Design
Prototype solutions built on scalable, cloud-native, and production-ready infrastructure using modular AI components.
6. Integration Readiness
Accelerate downstream deployment into your applications, APIs, or enterprise systems with reusable code, model pipelines, and deployment templates.
7. Cost Optimization
Experiment with open-source models (like LLaMA 3, Mistral, and Falcon) and efficient fine-tuning techniques (LoRA, QLoRA) to minimize compute costs.
8. AI Strategy Alignment
Inform your long-term GenAI strategy with hands-on experimentation, performance benchmarks, and data-driven insights—all tailored to your business.
Healthcare
- Clinical Document Automation – Generate discharge summaries, clinical notes, and diagnostic reports using patient data.
- Medical Chatbots – Provide symptom checking, appointment scheduling, and post-visit care via LLM-based virtual assistants.
- Drug Discovery Research – Use LLMs to analyze biomedical literature and identify novel therapeutic targets.
- Personalized Patient Communication – Tailor messaging and education materials to patient needs and language.
- Regulatory Compliance Review – Summarize and interpret compliance documentation for fast audit readiness.
Finance
- AI Financial Advisors – Build conversational agents for wealth planning and portfolio explanation.
- Risk Modeling & Stress Testing – Use LLMs to simulate scenarios based on real-world financial data.
- Automated Report Generation – Generate earnings reports, investment briefs, and audit summaries.
- Fraud Detection Insights – Enhance pattern recognition and anomaly detection with language-based context.
- KYC/AML Process Automation – Extract, validate, and classify customer data during onboarding.
Legal
- Contract Summarization – Use LLMs to extract obligations, risks, and clauses from complex legal contracts.
- Legal Research Assistants – Automate case law retrieval, statute search, and precedent analysis.
- Litigation Strategy Insights – Analyze previous rulings to assist in argument preparation.
- Compliance Document Drafting – Auto-generate GDPR, HIPAA, or regulatory templates.
- Client Communication Tools – Build chat interfaces that provide legal guidance within boundaries.
Retail & E-commerce
- Product Description Generation – Automatically create SEO-optimized product listings at scale.
- Customer Support Bots – Resolve queries, track orders, and manage returns via smart LLM agents.
- Market Trend Analysis – Summarize customer sentiment and competitor activity in real time.
- Personalized Shopping Recommendations – Use language cues to refine suggestion engines.
- Catalog Management Automation – Normalize and enrich product metadata using LLMs.
Logistics & Transportation
- Smart Route Optimization Summaries – Use LLMs to interpret real-time traffic and route suggestions for dispatchers.
- Freight Document Automation – Generate, verify, and summarize shipping and customs documentation.
- Customer Communication Assistants – Inform customers about delays, pickups, and changes in plain language.
- Predictive Maintenance Logs – Summarize sensor data and maintenance histories in human-readable form.
- Operations Control Chat Interfaces – Build LLM-powered command tools to manage fleets or shipping dashboards.
Education
- Curriculum Personalization – Use LLMs to tailor learning paths based on student performance, interests, and cognitive level.
- AI Teaching Assistants – Deploy virtual tutors for doubt resolution, assignment feedback, and adaptive learning.
- Content Summarization – Auto-summarize lecture notes, academic articles, and research papers into digestible insights.
- Admissions & Enrollment Automation – Streamline application processing, email correspondence, and document verification.
- Student Engagement Tools – Power chat-based learning apps that encourage interactive Q&A, quizzes, and gamified education.
Custom LLM Prototyping
We design, build, and evaluate LLM prototypes based on your business problem, domain-specific data, and desired user interaction—using the latest models like GPT-4o, LLaMA 3, Claude, and Mistral.
Domain Adaptation & Fine-Tuning
Enhance pre-trained models with your proprietary datasets to ensure accuracy, relevance, and compliance. We specialize in LoRA, QLoRA, and PEFT fine-tuning techniques.
Prompt Engineering & Optimization
Craft effective prompt structures, system instructions, and few-shot examples to improve model performance across tasks like summarization, Q&A, reasoning, and dialogue.
Evaluation & Benchmarking
We measure model performance, toxicity, bias, and hallucination rates using custom and open evaluation frameworks (e.g., HELM, TruthfulQA, MT-Bench).
Multimodal LLM Integration
Prototype LLMs that work across text, image, speech, or code. We help you integrate with tools like GPT-4o, Gemini 1.5, and OpenFlamingo for richer experiences.
LLM Infrastructure & Deployment
Build and deploy models using scalable frameworks like vLLM, TGI, Ray Serve, and KServe, optimized for cloud, on-prem, or hybrid environments.
Data Curation & Preprocessing
We assist in collecting, cleaning, and structuring text corpora, domain documents, chat logs, or other sources critical for training or evaluation.
Responsible AI by Design
We embed governance, ethics, safety, and compliance into every stage of our prototyping pipeline, aligned with ISO, GDPR, and AI Act standards.
Model Training & Fine-Tuning Frameworks
- Hugging Face Transformers
Industry-standard library for accessing, fine-tuning, and deploying pre-trained models like LLaMA, Falcon, and Mistral. - PEFT (Parameter-Efficient Fine-Tuning)
Enables scalable tuning using LoRA, QLoRA, and Prefix Tuning—ideal for domain adaptation with minimal compute. - DeepSpeed & FSDP (Fully Sharded Data Parallel)
Accelerates large-scale training with GPU memory optimization and parallel compute. - Axolotl / Lit-GPT / Colossal-AI
Lightweight frameworks for rapid experimentation with LLM fine-tuning and pretraining on custom corpora.
Serving & Inference Frameworks
- vLLM
High-throughput inference engine for serving LLMs efficiently, with support for continuous batching and multi-user access. - Text Generation Inference (TGI)
Production-grade serving system optimized for Hugging Face models, offering token streaming and multi-GPU support. - Ray Serve & KServe
Scalable microservice-based deployment platforms for managing LLM workloads on Kubernetes or hybrid cloud. - LangChain / LlamaIndex
Frameworks for building LLM-powered applications, including RAG (Retrieval-Augmented Generation), chatbots, and agents.
Evaluation & Safety Tooling
- OpenLLM Leaderboards / HELM
Benchmarking tools for evaluating performance, cost, latency, and ethical risk across LLMs. - MT-Bench & TruthfulQA
Test models for reasoning, hallucination, and truthfulness, critical for safe enterprise deployment - Guardrails AI / Rebuff
Add runtime protections and safe output filtering to your LLM applications.
Data & Preprocessing
- DVC / Weights & Biases
Track experiments, datasets, and model artifacts across your training workflows. - FastText / spaCy / NLTK
Used for linguistic analysis, data cleaning, and tokenization during model preparation. - Apache Airflow / Prefect
Orchestrate complex data pipelines that support model training and deployment stages.
What Sets Us Apart
Deep Research DNA
We stay ahead of the curve by actively contributing to LLM research, including prompt optimization, fine-tuning techniques, safety alignment, and multi-modal prototyping.
Full-Stack AI Engineering
From data ingestion and fine-tuning to serving infrastructure and inference optimization, we deliver end-to-end solutions tailored to your enterprise context.
Model-Agnostic Expertise
We work across leading LLMs—OpenAI (GPT-4o), Meta (LLaMA 3), Anthropic (Claude 3), Mistral, and open-source custom models—matching the right tool to your goals.
Responsible AI Focus
Our solutions embed privacy, governance, and ethics by design, helping you stay compliant with GDPR, AI Act, and evolving regulatory frameworks.
Rapid Prototyping Culture
We help clients move from idea to prototype in under 4–6 weeks, using agile methods, fast iteration cycles, and reusable components for quick experimentation.
Real Business Outcomes
Our LLM solutions are built to deliver measurable value—faster operations, better decisions, and enhanced customer experiences across industries.
Collaborative Partnership
We don’t just build and leave. Our team co-creates solutions with your domain experts, iterates quickly, and ensures knowledge transfer for long-term success.
