Tiny Script Soft Tech

AI & Machine Learning Development Services

Tiny Script Soft Tech is an innovation-driven AI and machine learning development company in Ahmedabad, Gujarat. We engineer state-of-the-art Artificial Intelligence solutions, custom Large Language Model (LLM) integrations, Retrieval-Augmented Generation (RAG) platforms, predictive analytics engines, and intelligent process automation tailored for enterprise scale.

Our Artificial Intelligence & Machine Learning Capabilities

  • Generative AI & Enterprise LLMs: Custom AI applications built with OpenAI (GPT-4o), Anthropic Claude, Meta LLaMA 3, and Mistral models fine-tuned on your domain knowledge.
  • Retrieval-Augmented Generation (RAG): Enterprise knowledge base chatbots that retrieve answers strictly from your private documents, PDFs, manuals, and databases with zero hallucinations.
  • Custom AI Agents & Autonomous Workflows: Multi-agent systems that research, synthesize information, update CRMs, generate reports, and execute complex business tasks autonomously.
  • Machine Learning & Predictive Modeling: Algorithms engineered for customer churn prediction, dynamic pricing, sales forecasting, demand planning, and fraud detection.
  • Computer Vision & Document OCR: Automated document extraction, facial recognition, visual quality inspection, invoice data extraction, and video intelligence.
  • Natural Language Processing (NLP): Sentiment analysis, automatic summarization, multi-language translation, and intent classification for customer service.

Our AI Engineering Process

  1. Business Use-Case Discovery: Identifying high-impact automation opportunities and calculating feasibility and ROI.
  2. Data Auditing & Preprocessing: Cleaning, structuring, anonymizing, and embedding proprietary business data into high-performance vector databases.
  3. Model Architecture & Prototyping: Building rapid Proof-of-Concept (PoC) models in 2 to 3 weeks to validate output accuracy and performance.
  4. API Integration & Production Hardening: Deploying low-latency microservices with GPU orchestration, token caching, and rate limiting.
  5. Continuous Fine-Tuning & Monitoring: Real-time monitoring of response latency, drift detection, and automated human-in-the-loop validation.

AI Frameworks & Tech Stack

Our AI engineers work with PyTorch, TensorFlow, Hugging Face, LangChain, LlamaIndex, Python, FastAPI, Pinecone, Qdrant, Milvus, ChromaDB, OpenAI API, Claude API, Docker, and AWS SageMaker.

Frequently Asked Questions (FAQ)

How can custom AI solutions benefit our business?

Custom AI automates repetitive tasks, reduces operational overhead by up to 60%, extracts instant insights from unstructured enterprise data, delivers 24/7 intelligent customer support, and enables predictive decision-making.

Can you build AI chatbots trained on our private proprietary data?

Yes. We use Retrieval-Augmented Generation (RAG) and private vector embeddings to connect AI models to your proprietary documents and databases without your sensitive data ever being used to train public models.

How long does it take to develop an AI Proof of Concept (PoC)?

A functional AI Proof of Concept (PoC) typically takes 2 to 4 weeks. Once validated, full enterprise integration usually follows in an 8 to 12-week implementation roadmap.

How do you prevent AI hallucinations in enterprise applications?

We implement strict guardrails, temperature controls, prompt constraints, vector similarity thresholds, and source citation verification so answers are strictly grounded in your verified reference data.