Inseed

Written by: Umar

30 June 2025

AI at Work – How Inseed is Building Smarter Digital Solutions Every Day

Artificial Intelligence is no longer the future it's now. At Inseed Tech Pvt Ltd, we’ve made AI an integral part of our digital strategy, product development, and internal operations. From automating manual tasks to transforming user experience through personalized recommendations, we believe in building AI for impact not just hype.

This blog explores how Inseed integrates AI into real-world applications, the tools we use, and the principles guiding our AI-driven approach.

How We Use AI at Inseed?

Product Features: We implement AI in client applications such as intelligent chatbots, smart search engines, and recommendation systems.
Automation: Internally, we use AI to automate reporting, daily scheduling, resume filtering, and more.
Development Workflows: Brainstorming ideas, generating code snippets, and reviewing technical documentation.
Design Acceleration: Tools like Midjourney and DALL·E are used to generate initial design inspiration, saving hours of manual sketching.

Our AI Tech Stack

OpenAI GPT-4o: Content generation, brainstorming, documentation support.
Google Cloud Vertex AI: Custom model training, real-time predictions.
Azure Cognitive Services: For OCR, speech-to-text, and emotion detection.
TensorFlow / PyTorch: Deep learning model development.
Zapier + AI: Automated workflows for emails, reminders, task updates.
Midjourney / DALL·E: Design generation and visual prototyping.

Case Study: Reducing Support Load with AI Chatbot

For a SaaS client, we implemented an AI-driven chatbot integrated with the company’s knowledge base. Within 60 days, support ticket volume dropped by 40%, and customer satisfaction improved significantly.

Challenges We Tackle with AI

Data Bias: We monitor our models to avoid reinforcing harmful patterns.
Explainability: Our AI is transparent and auditable.
Scalability: We ensure AI features can handle traffic and data growth.

What’s Next?

Inseed is currently working on integrating AI into analytics dashboards to deliver predictive insights to end users. We’re also exploring AI-assisted QA testing and performance tuning.