Deploying An Engineer Support Agent
For Heavy Machining Operations On Aws

Suraj Microtech Engineers is a heavy-machining and precision engineering shop supplying components to power generation, cement, steel, and petrochemical industries. Their production floor runs a large and fragmented fleet of machines from multiple manufacturers and generations, making troubleshooting slow and inconsistent.lambertlabs+1

Technicians currently find troubleshooting answers by manually searching printed manuals, shared drives, or asking senior colleagues. This process takes time, depends on individual experience, and directly contributes to machine downtime and inconsistent first-time-fix outcomes.

With no central source of truth, two technicians might solve the same problem differently, and critical knowledge is often lost when senior staff leave.

Silicon Power Solutions worked with Suraj Microtech Engineers to identify the root causes of delayed troubleshooting and design a solution that gives technicians immediate access to accurate, source-cited answers.

The goal was to reduce search time, standardize responses, and preserve institutional knowledge in a way that scales across shifts and new hires.

We deployed an Engineer Support Agent using Amazon Bedrock, Bedrock Knowledge Bases, and Amazon S3 Vectors for semantic retrieval over the full equipment documentation corpus.

The system ingests manuals, SOPs, and technical documents into a searchable knowledge base. When a technician asks a question, the agent retrieves the most relevant passages and returns a near-instant, source-cited answer via Bedrock AgentCore Runtime and DynamoDB.lambertlabs+1

This approach ensures that every answer is grounded in verified documentation, reduces reliance on individual memory, and speeds up resolution across the plant.

Suraj Microtech Engineers now has a smarter way to access technical knowledge. Technicians can get immediate, accurate answers without waiting for senior staff or digging through scattered files.

The new system reduces machine downtime, improves first-time-fix rates, and creates a scalable foundation for onboarding new technicians and expanding to additional shops.