01
About Soban
From computer vision pipelines that took object detection accuracy from 63% to 90% on 50,000+ construction images, to a 13-agent LLM orchestration system designed to eliminate tool-routing errors in complex workflows.
My work sits at the intersection of applied ML and infrastructure: I've shipped autonomous forecasting platforms with automated CI/CD retraining, built agentic RAG systems with FAISS for large-scale tool routing, and deployed cloud-native ML APIs on GCP.
Read more
Always exploring new problems at the intersection of applied AI and its business use cases, happy to connect with people building in this space.
Professional profile
- Location
- Pakistan
- Time zone
- Asia/Karachi
- Work mode
- Remote
- Availability
- Available Now
- AI experience
- 2+ years
- Industry experience
- 2+ years
- Languages
- English
- Working hours
- 03:00-12:00 AM GMT, Mon-Fri
- Typical response
- Within a few hours
- Preferred engagement
- Small (individual or single team)
- Travel
- Occasional travel
02
Proven on the network
Implementation records and publicly available work, where published.
0 AI Deployments delivered. No publicly identified implementations are available to inspect.
03
What Soban builds
Implementation domains listed on this profile. Evidence-supported items are identified separately below.
Specialisations
Agentic Workflow Automation
AI Agents
Computer Vision
Document Intelligence
Multi-Agent Systems
04
AI Deployments
Real AI implementations demonstrated through evidence.
No publicly identified Deployments are available to inspect.
05
Implementation capabilities
Evidence-supported means linked to a published Deployment or Case Study; other capabilities are Builder declared.
Evidence-supported
No published evidence linked yet.
Builder declared
- Agentic Workflow Automation
- AI Agents
- Computer Vision
- Document Intelligence
- Multi-Agent Systems
06
Industry experience
Published Deployments support the listed counts. Other industries are Builder declared.
Architecture & Engineering
Builder declared
Clinical Research Organizations (CROs)
Builder declared
Construction
Builder declared
Logistics & Transportation
Builder declared
Manufacturing
Builder declared
07
Trust & verification
A closer look at how this profile and its evidence are reviewed.
Community Member
Published evidence is reviewed against the AI Deploy Network Evidence Standard.
How verification works
Verified Builder
Independently reviewed by AI Deploy Labs against the platform Evidence Standard.
How this is verifiedWhat the platform has established, and what remains builder-declared.
- Identity and organisation
- Identity checks confirm that the person presenting this profile controls the account and the professional identifiers attached to it, such as a LinkedIn profile. Organisation membership is confirmed by the organisation, not self-declared by the builder.
- AI Deployments
- An approved AI Deployment is an implementation record the builder submitted and the platform reviewed against the Evidence Standard before publication. Approval confirms the record is complete, coherent and consistent with the supporting material provided — it is not an audit of the client's systems.
- Business outcomes
- Outcome figures are recorded by the builder on the deployment or case study that produced them, and are reviewed at publication. Aggregates shown on this profile are calculated from those approved records only.
- Evidence
- Supporting evidence comes from the records the builder published on this platform: approved AI Deployments, published AI Case Studies, verification outcomes and organisation participation.
- Currency
- Older evidence continues to count and is never removed. Recency is presented separately through Professional Currency so that current expertise can be assessed alongside historical work.
- Traceability
- Every figure on this profile can be followed to the record that produced it. Open the linked AI Deployment or AI Case Study to read the outcome exactly as it was reported.
The platform does not independently audit client systems or financial records. How this is verified
Professional record and further evidence
Client Portfolio
Portfolio started
Gatronova
Automation • Logistics & Transportation
Pakistan2026- Delivered a vehicle health analytics dashboard, aggregating and surfacing insights from 20+ data sources in real time. - Automated PDF-based data extraction and analysis, saving the organization 60+ hours of manual work per month. - Designed the automation to run unattended, cutting a previously manual reporting process down to a repeatable pipeline.
Construction Company
ConfidentialComputer Vision • Construction
United States2026-Automated architectural cost and labor estimation for construction project bidding, eliminating a fully manual workflow. - Owned the end-to-end ML pipeline - from multi-stage data annotation through model deployment, for a dataset of 50,000+ images. - Boosted object detection accuracy from 63% to 90% through model tuning and strategic data augmentation. - Integrated ML-assisted annotation to cut labeling time and improve dataset quality.
Professional Certifications
Some recognitionMicrosoft Certified: Azure AI Apps and Agents Developer Associate
Microsoft
Issued Sep 2026
Credential ID: 21A8957206076362
Ready to discuss your AI implementation?
Tell Soban what you are trying to automate and the outcome you need. Your message goes directly to the builder, with a copy kept in your Organisation Workspace.