Content Generation & Summarization
LLM-powered content creation, document summarization, and report generation fine-tuned to your brand voice.
Technobots Services
NLP & Generative AI
Natural language processing (NLP) lets software understand and generate human language. Generative AI — large language models (LLMs) — can draft content, summarise long documents and answer questions. Retrieval-augmented generation (RAG) connects an LLM to your own documents so its answers are grounded in your data. Technobots builds these systems for your business, tuned to your brand voice and your knowledge base.
What we build
Sentiment & Text Analytics
Analyze customer feedback, reviews, and social media at scale to uncover sentiment trends and insights.
Semantic Search & RAG
Build intelligent knowledge bases with retrieval-augmented generation for natural-language Q&A.
Where it helps
Company knowledge assistant
Let staff ask questions in plain language and get answers from your own policies and documents.
Report & document summaries
Turn long reports, contracts and transcripts into short, accurate summaries.
Customer feedback analysis
Understand what customers are saying across reviews, surveys and social media.
Content at scale
Draft product descriptions, emails and reports in your brand voice for human review.
How we work
- Discovery. We learn your goals, current process and data, and agree what success looks like.
- Design. We choose the right models and architecture and share a clear scope before building.
- Build & integrate. We develop the solution and connect it to the systems your team already uses.
- Deploy & measure. We launch with dashboards and KPIs so you can see the impact in real time.
- Support & improve. We monitor, maintain and improve the solution after launch.
Technologies
Frequently asked questions
What is RAG (retrieval-augmented generation)?
RAG is a way of connecting a large language model to your own documents. When someone asks a question, the system first finds the most relevant passages in your knowledge base, then has the LLM answer using only that information — which makes answers more accurate and lets you cite the source.
Will generative AI make things up?
LLMs can produce confident but wrong answers. We reduce this by grounding answers in your documents with RAG, adding guardrails, and testing against real questions before launch.
Can you use our documents without sharing them publicly?
Yes. Your documents stay private to your system and are used only to answer your users' questions.
Which AI models do you use?
We choose the model per project — for example OpenAI models or open-source models from HuggingFace — based on accuracy, cost, language and privacy requirements.
Related services
Talk to us about NLP & Generative AI
Tell us what you want to achieve and we'll get back to you. Prefer to talk? Call or WhatsApp +91-9286133120.