Artificial Intelligence is no longer a buzzword — it’s the engine behind faster decisions, deeper personalization, and scalable automation. At TAS, we turn powerful models like GPT-4o, Claude, and open-source LLMs into real business tools — from customer-facing chatbots to intelligent document workflows and AI agents that automate entire roles.
🚀 Build with AI that Works — Not Just Experiments
We work with startups, enterprises, and product teams who want real impact from AI — not just demos. Whether you need a plug-and-play chatbot, a custom-trained assistant, or a fully autonomous backend worker — we bring the engineering depth, the AI strategy, and the speed to ship.
🧠 What We Deliver
🤖 1. AI Agents & Autonomous Workflows
Agents that think, act, and automate:
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Custom AI agents with memory, multi-step reasoning & tool use
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Sales & marketing automation (auto-email replies, lead qualification)
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Internal taskbots that schedule, update CRMs, or trigger business actions
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Code + no-code agent deployment with LangChain, CrewAI, and FastAPI
✅ Project Example: Internal AI agents for job applicant parsing and HR screening — reviewed 5,000+ resumes and matched candidates to roles using GPT and embeddings.
💬 2. AI Chatbot & Voicebot Development
We build multilingual, intelligent bots for:
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Customer support & helpdesk
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Internal knowledge assistants
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Lead generation on websites
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Voice-to-chat support for call centers
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WhatsApp, Telegram, CRM, website, and mobile integrations
✅ Project Example:
AI-Based Voice Analysis System for Rural India — Users speak in Hindi or local dialects, system converts to text, answers using GPT, and speaks back in local language using TTS — used in healthcare and legal advisory projects.
📚 3. LLM / OpenAI Integration
We help you build, embed, or fine-tune LLMs:
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OpenAI (GPT-4o, GPT-3.5), Claude, Gemini, Mistral, LLaMA
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Custom GPTs via OpenAI Assistants API
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Self-hosted LLMs for sensitive data
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Prompt engineering, memory, safety filters, & guardrails
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Cost-optimized deployment via API gateways or batching
✅ Project Example:
EHR Automation for Multilingual Medical Transcription — Doctor voice notes transcribed using Whisper, summarized using GPT, structured into EHR-ready format. Delivered across multiple Indian languages.
🔍 4. Retrieval-Augmented Generation (RAG) Systems
Make your LLMs answer based on your data:
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Connect PDFs, internal docs, knowledge bases, websites
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Use vector databases like Pinecone, Qdrant, FAISS
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Fully private / hosted / cloud-based options
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Embedded inside dashboards, support systems, or apps
✅ Project Example:
Internal enterprise knowledge assistant trained on company handbooks and support tickets, enabling staff to ask real-time questions with source traceability.
📄 5. AI Document & Workflow Automation
Replace manual processes with smart AI logic:
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AI-generated reports, summaries, emails, invoices
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Resume parsers, legal doc summarizers
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Image captioning or OCR + LLM workflows
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Healthcare reporting, financial insights, academic processing
✅ Project Example:
Resume screening + JD matching tool with GPT-powered scoring, AI auto-generated candidate feedback, and recruiter prompts.
🔧 Tools & Technologies We Use
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LLMs: GPT-4o, Claude 3, Gemini Pro, Mistral, LLaMA
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Frameworks: LangChain, LlamaIndex, FastAPI, CrewAI
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Voice AI: Whisper, Coqui, Google TTS/STT
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Vector DBs: Pinecone, Qdrant, FAISS, Weaviate
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UI & Infra: Streamlit, Next.js, Vercel, Docker
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Integrations: Zapier, Notion, Slack, WhatsApp, Email, CRMs
📈 AI Projects from the TAS Portfolio
🏥 Multilingual Medical Transcription & EHR Automation
Voice-to-structured-text pipeline for doctors — includes Whisper transcription, GPT summarization, local language processing, and output to EMR/EHR.
🗣️ AI-Based Voice Assistant for Rural Helpdesk
Real-time voice bot for rural support services. Converts user questions into text, generates GPT-based answers, and speaks them back in the user’s language.
📄 AI Powered LP Scanner and Yield Farming System
Built an AI-driven platform that automatically discovers, ranks, and executes high-APY yield farming opportunities across Ethereum and Solana using machine learning and smart contracts.
🧩 Smaller AI Services We Also Offer
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Custom GPT builders using OpenAI Assistants API
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AI-powered search interfaces for websites
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Internal chatbot systems for HR, operations, finance
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Prompt optimization & safety audits
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AI-powered knowledge bases with versioning & memory
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Fine-tuning of open-source models using your datasets
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LLM architecture consulting & infrastructure setup
✅ Why Choose TAS for AI/ML Integration?
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💡 Strategy + Execution – We help you define the right AI use case, then build it to scale.
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🛠️ Full-Stack Team – From model to dashboard to deployment.
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🔐 Enterprise-Ready – Secure, documented, and testable code.
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⚙️ Rapid MVPs – Launch in weeks, not quarters.
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📊 AI + Domain Expertise – Finance, health, HR, ecommerce, and media.
❓ AI Agents / GPT / LLM Integration – FAQs
Q1. What is AI agent and LLM integration?
AI agent and LLM integration involves embedding advanced Large Language Models (LLMs) like GPT, OpenAI, and Hugging Face Transformers into your applications. This enables features such as chatbots, virtual assistants, automated workflows, knowledge search, and personalized recommendations.
Q2. Why should I choose TAS for AI agent & GPT integration?
TAS has deep expertise in AI/ML, natural language processing (NLP), and enterprise integrations. We don’t just plug in APIs — we customize AI agents, fine-tuned models, and RAG (retrieval-augmented generation) systems to fit your business workflows securely and at scale.
Q3. What kind of AI-driven apps can you build?
We develop intelligent chatbots, AI customer support systems, voice assistants, document summarizers, automated research tools, recommendation engines, and DeFAI systems powered by GPT and other LLMs.
Q4. How long does it take to integrate GPT or LLMs into an app?
A basic chatbot or text automation can be integrated in 2–4 weeks, while enterprise-grade AI assistants or knowledge platforms may take 2–4 months, depending on complexity and integrations.
Q5. What technologies do you use for LLM integration?
Our stack includes OpenAI GPT models, LangChain, Hugging Face Transformers, Pinecone, Weaviate, Vector DBs, Python (FastAPI), Node.js, and cloud platforms (AWS, GCP, Azure) for scalable deployments.
Q6. How do you ensure data privacy and compliance?
We implement secure APIs, data anonymization, encryption, and compliance with GDPR/HIPAA/SOC2 standards. We can also set up private LLM deployments for sensitive enterprise data.
Q7. How much does AI agent or GPT integration cost?
The cost depends on model choice, level of customization, and infrastructure needs. Basic integrations start from a few thousand dollars, while custom-trained LLM apps require higher investment. We offer flexible pricing tailored to your goals.
Q8. Do you provide post-launch support and model optimization?
Yes. We provide continuous monitoring, fine-tuning, model retraining, feature upgrades, and performance optimization to keep your AI systems accurate and effective over time.
📞 Let’s Build AI That Solves Real Problems
At TAS, we don’t just bolt on AI — we engineer it into the core of your product. If you’re building something serious with GPT, agents, or automation, we’re the team that delivers.
