AI Development
AI Deployment Machine Learning Google Cloud
Confidential
Mar. - May 2026

5.0

Quality: 5.0

Schedule: 5.0

Cost: 5.0

Willing to Refer: 5.0

"What impressed us most about Transcloud Labs was their responsiveness, professionalism, and willingness to help."

Oct 19, 2026

Co-Founder & CTO, Mutanex

Nishant Vaja

Other industries
India
1-10 Employees
Online Review
Verified

Transcloud Labs developed an AI pipeline tool for a precision medicine company. The team's solution standardized information from laboratory reports into JSON format using Google Cloud Document AI and Gemini.

Transcloud Labs delivered a solution that produced consistent JSON structures and reduced data processing by 99.85%, saving costs. The team was responsive, professional, and helpful in addressing the client's needs. Moreover, Transcloud Labs was collaborative and committed to customer satisfaction.

The client submitted this review online.

BACKGROUND

Please describe your company and position.

I am the Co-Founder & CTO of Mutanex

Describe what your company does in a single sentence.

Mutanex is a precision medicine company building AI-powered healthcare intelligence to make personalized, proactive care accessible to everyone. By bringing together medical reports, clinical history, laboratory results, and eventually genomic and imaging data, Mutanex helps connect health findings, identify potential underlying causes, track changes over time, and guide doctors toward evidence-based decisions. Our vision is to transform fragmented medical data into a continuous, personalized understanding of each individual’s health, moving healthcare from reactive treatment to prevention and precision.

- From longevity to precision

OPPORTUNITY / CHALLENGE

What specific goals or objectives did you hire Transcloud Labs to accomplish?

We needed a reliable way to extract information from medical laboratory reports and convert it into a standardized JSON format that our other systems could use directly. The reports arrived as PDFs and images, with each laboratory using different layouts and terminology for the same tests. Our primary objective was to accurately extract patient details, test names, results, units, and reference ranges across these variations while reducing the manual effort involved in processing reports.

SOLUTION

How did you find Transcloud Labs?

Google For Statups

Why did you select Transcloud Labs over others?

Pricing fit our budget
Great culture fit
Good value for cost
Referred to me
Company values aligned

How many teammates from Transcloud Labs were assigned to this project?

2-5 Employees

Describe the scope of work in detail. Please include a summary of key deliverables.

The project involved building an AI-powered pipeline to extract and standardize information from medical laboratory reports. Since reports arrived as PDFs and images with varying layouts, table structures, and test names, the solution needed to handle these differences while producing consistent, structured data. Transcloud developed a document processing pipeline using Google Cloud Document AI and Gemini. Document AI extracted text, tables, and relevant fields from the reports, while Gemini interpreted the extracted information and mapped it into a predefined JSON schema. The team also evaluated MedGemma to determine its suitability for the requirements. Following this evaluation, Document AI and Gemini were selected to address the document extraction and data mapping needs. To improve processing efficiency, Transcloud introduced a custom filtering step that passed only relevant data to Gemini. This reduced the amount of data the model needed to process, improved accuracy and opimized performance. Key deliverables included the document extraction pipeline, and field-level confidence scores to flag extracted values that might require manual verification.

RESULTS & FEEDBACK

What were the measurable outcomes from the project that demonstrate progress or success?

We tested the solution on more than 400 real laboratory reports, with fewer than 1% failing to extract correctly. The pipeline produced a consistent JSON structure across different report layouts, allowing other applications to consume the extracted information directly. One notable improvement was the reduction in data passed to Gemini. For one sample report, the filtering process reduced the input from 18.5 MB to 28 KB, approximately 99.85% less data. This has helped to reduce the amount of data processed by the model and lowered API costs. The pipeline also assigns confidence scores to individual extracted fields, allowing values with lower confidence to be flagged for manual review rather than accepted without verification. Overall, the solution has reduced the manual effort involved in reading laboratory reports and entering results into other systems.

Describe their project management. Did they deliver items on time? How did they respond to your needs?

Transcloud demonstrated good project management by successfully delivering the project requirements for report extraction. They have been responsive to our requirements and continue to provide support even after the PoC was completed. Their team has been helpful in addressing our needs and providing ongoing assistance. Overall, we have had a positive experience working with Transcloud.

What was your primary form of communication with Transcloud Labs?

Virtual Meeting
Email or Messaging App

What did you find most impressive or unique about this company?

What impressed us most about Transcloud Labs was their responsiveness, professionalism, and willingness to help. They respond promptly and courteously, take the time to understand the problem, and focus on finding practical solutions rather than creating unnecessary roadblocks or focusing solely on commercial considerations. They are also willing to go beyond the defined scope of work when needed to achieve the best possible results. Their collaborative, solution-oriented approach and commitment to customer satisfaction make them a valuable partner.

Are there any areas for improvement or something Transcloud Labs could have done differently?

The main area for improvement is reducing the time taken to start a PoC. In our case, it took a bit longer than usual from the initial discussion to kickoff, which impacted the expected deliverables. Stronger coordination with Google and clearer timelines could help speed up the process and ensure a smoother experience.

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5.0

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