Auranik

AI & Automation

AI ও অটোমেশন সলিউশন

কোম্পানির তথ্য, ডকুমেন্ট আর ভেতরের কাজকর্ম সহজ করতে কাজের AI, শুধু আলোচনার জন্য নয়, বাস্তব ব্যবসায়িক কাজে।

Discuss an AI Project

01

The problem we solve

Teams lose time searching documents, answering the same internal questions and re-typing information between systems, while public AI tools raise questions about where company data goes.

We build AI assistants and automations around your own documents and processes, with access controls and private deployment options, so useful automation does not come at the cost of control.

02

Useful AI applications

  • Private AI assistants
  • Company knowledge search
  • RAG solutions
  • Document intelligence
  • Workflow automation
  • Internal support assistants
  • Local/private LLM deployment
  • AI integration

03

What you gain

  • Faster answers from your own documents and knowledge base
  • Less manual re-typing between documents and systems
  • Clear rules on who can access which data
  • A pilot scoped to one measurable process before wider rollout

04

How we work

  • Technical discovery: the business problem, current environment, constraints and delivery model
  • Assessment: systems, cloud, field or staffing requirements reviewed against that context
  • Solution design: architecture, resource profile or delivery approach agreed in writing
  • Implementation coordination: engineering work, deployment, escalation and reporting
  • Optimisation and support: monitoring, cost control, documentation and ongoing improvement

05

Governance first

We focus on controlled access, clear use cases and business processes where AI can support work without replacing accountability.

FAQ

Can AI run on our own infrastructure?

Yes. Local and private LLM deployment is one of the options, so documents do not need to leave your environment.

What is RAG?

Retrieval-augmented generation: the assistant first finds the relevant passages in your documents, then answers from them, which keeps answers grounded in your own sources.

Where should we start?

With one well-defined process, such as internal knowledge search or document extraction, where the benefit can be measured before scaling.

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