Advanced Artificial Intelligence (AI) Solutions

We build AI chatbots for customer support and lead generation, enterprise AI assistants for internal workflows, AI-powered document search, private knowledge assistants, workflow automation tools, and offline local LLM systems that run on your own infrastructure.

Yes. We can build a customer-facing AI chatbot that answers questions, qualifies leads, collects details, books calls, and routes conversations to your team. The chatbot can be trained on your website, FAQs, product content, documents, and service process, with CRM or backend integrations where needed.

A normal chatbot usually answers public customer questions. An enterprise AI assistant works with internal business knowledge and team workflows. It can search policies, summarize documents, draft responses, retrieve customer or operational context, and automate repeated internal tasks while respecting user roles and data permissions.

Yes. For organizations with strict privacy or compliance needs, we can deploy local LLM systems on private infrastructure. That means sensitive documents, prompts, and responses stay inside your environment. The tradeoffs are infrastructure cost, model capability, and maintenance, which we evaluate during discovery.

A focused AI chatbot or internal assistant can often be built in 4 to 8 weeks. More complex enterprise systems with private knowledge bases, multiple roles, integrations, audit requirements, or offline LLM deployment take longer. We usually start with a scoped pilot so your team can validate usefulness before expanding.

Advanced Artificial Intelligence (AI) Solutions currently start at ₹2,67,000. Final cost depends on the workflow, data sources, integrations, and deployment model. A focused website chatbot or internal assistant is usually scoped as a pilot first. Enterprise AI systems with private knowledge bases, custom tools, role-based permissions, or local LLM infrastructure cost more because the architecture, testing, and security requirements are heavier.

Yes. We can connect AI assistants with CRMs, websites, admin panels, backend APIs, document systems, support tools, and internal dashboards. The assistant can answer questions, collect structured information, create leads, summarize records, or trigger approved workflows depending on what your systems allow.

Yes, when the use case requires it. We can connect approved documents, FAQs, policies, product data, support content, spreadsheets, or database records through a controlled knowledge layer. For sensitive data, we define access rules so users only get answers from information they are allowed to see.

The model depends on the job. Some use cases work best with hosted frontier models, some can use smaller cost-efficient models, and privacy-sensitive workflows may need local LLMs. We choose based on answer quality, latency, cost, data privacy, language needs, and infrastructure constraints rather than forcing one model for every project.