Software bots handle repetitive, rule-based tasks: data entry, file movement, form submission, and system-to-system transfers. Bots run faster than manual processing and produce consistent output every time.
Automate Repetitive Work with AI and RPA
Tekgen builds custom intelligent automation solutions that combine robotic process automation, machine learning, and AI to free your team from manual work and let your systems handle the routine.
Custom AI and Automation for Modern Operations
Repetitive data entry, copy-paste work between systems, and manual document processing consume time that your team could spend on work that actually requires judgement. Tekgen, based in Ahmedabad, India, builds custom intelligent automation systems that combine robotic process automation (RPA), machine learning, and AI to convert those bottlenecks into self-running workflows. (/contact)
The work covers the full picture: from mapping the processes worth automating, to building the bots or models that handle them, to keeping those systems running after launch. Tekgen works best with startups and growing businesses that want a single partner responsible for a product from first design through post-launch support, rather than handing off between separate strategy, build, and maintenance vendors. (/about)
What gets automated
The most common starting points we see:
- Data extraction from invoices, contracts, and forms, feeding structured output into your existing systems
- Document routing and approval workflows that currently stall waiting for someone to click forward
- Customer-facing or internal assistants that answer questions from your own content, with a handover path to a person when needed
- Classification and tagging pipelines that sort tickets, emails, or records at volume
How RPA and AI fit together
RPA handles rule-based, predictable tasks: it works faster than manual processing, produces fewer errors, and delivers the same result every time. Cognitive automation goes further, using AI and ML to handle inputs that vary, things like unstructured text, scanned documents, or decisions that depend on context. Process mining sits beneath both, finding where the actual inefficiencies are before any automation is built.
For teams exploring how AI can extend automation beyond fixed rules, the Generative AI and LLM Development Services page and the Intelligent Automation: RPA, AI and Process Mining page both cover how Tekgen applies these technologies in practice, and the Cloud, AI and Software Development Blog publishes practical guides on RAG and AI agents for readers who want to go deeper.
Intelligent Automation Services
Tekgen's automation practice covers three core capability areas, applied across sectors including healthcare and life sciences, finance and banking, logistics, retail, and more.
- Robotic process automation
- Cognitive automation
AI and ML models handle inputs that don't follow fixed rules, unstructured documents, natural language queries, and decisions that depend on context, so automation extends beyond the tasks RPA alone can reach.
- Process mining and optimization
Before building anything, we map your actual workflows using process mining tools to find where time is lost and which processes will return the most from automation.
- AI chatbots and assistants
Assistants for customers or staff that answer from your own content, hand over to a person when they should, and keep a log of every conversation.
- RAG-powered document search
Search and question-answering over your documents, wikis, and tickets, with answers that cite the source they came from. Useful for internal knowledge bases, compliance documents, and support teams.
- Document processing and data extraction
Pulling structured data out of invoices, contracts, forms, and emails, with confidence checks and a review step for anything uncertain. Output connects directly to your existing systems.
The Six-Stage Delivery Process
Every automation engagement follows the same six stages, with a written proposal agreed before work starts and support continuing after launch.
- 1. Assessment and strategy
We map your current processes, identify which are worth automating and in what order, and produce a prioritized list before any build work begins.
- 2. Use case and data review
We agree on one concrete job for the AI or automation to do, and check that the data it needs exists and can be used. Scope is set in writing before the prototype starts.
- 3. Prototype
We build a working prototype on a sample of your data so you can judge real outputs early, before committing to the full production build.
- 4. Evaluation
We build a test set of real questions or inputs and score the system against it before and after every change, so quality is measured, not assumed.
- 5. Production build
We add authentication, logging, cost limits, and guardrails, then connect the system to your product or existing infrastructure.
- 6. Monitoring and support
After launch, we track answer quality, cost, and usage, improve weak spots, and keep the system updated. Support is available Monday to Friday, 10:00 to 20:00 IST.
Questions on Scoping, Data Security, and Post-Launch Maintenance
How much will the project cost?
Project cost depends on scope. We quote each project after we understand your goals, and you get a written proposal with the cost before any work starts. Send us what you need and we reply within one business day.
How long will the project take?
Timelines depend on scope, so we set them in the written proposal along with the cost, before work starts. If you have a fixed launch date, mention it in your enquiry so the proposal accounts for it.
Will our data be used to train public AI models?
Not through anything we set up. We use business API terms or cloud-hosted models (Azure OpenAI, Amazon Bedrock, Vertex AI) where your data is not used for training, and we can run open models on your own infrastructure if you prefer.
How do you stop the AI producing wrong answers?
We ground answers in your own documents, show the sources, tell the model to say when it does not know, and test against a set of real questions before launch. No system is perfect, so we also design how mistakes get caught after launch.
Who owns the code and the designs?
Ownership of everything we build for you is set out in your project agreement, which you see and agree to in writing before work starts.
More on our site
- Intelligent Automation: RPA, AI & Process Mining - Tekgen
Tekgen's intelligent automation page covers RPA, cognitive automation and process mining — the closest match to an AI & Automation Services topic.
- Generative AI & LLM App Development Services - Tekgen
Tekgen's generative AI and LLM development service covers chatbots, RAG and AI features that fall directly within AI & Automation Services.
- Software Development Services
Tekgen's full services page lists all 34 offerings including AI agents, data engineering and DevOps, giving broader context for the AI and automation work.
- Cloud, AI and Software Development Blog - Tekgen
The blog publishes practical guides on RAG, AI agents and LLM apps, which readers of an AI & Automation Services page would find directly useful.
- About Tekgen: Custom Software Company in India
The About page explains Tekgen's background delivering AI and cloud solutions, relevant for readers wanting to know who provides these services.
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