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Giggso Tech Stack
AI governance and MLOps consulting for enterprise digital transformation
Giggso pairs AI/ML consulting with governance expertise, positioning itself between traditional IT advisory and applied ML engineering. The tech stack reflects a services-heavy footprint (multi-cloud, Salesforce, infrastructure-as-code tooling) rather than a single-product platform. Active hiring in engineering and data roles—concentrated at senior and lead levels—suggests they're scaling delivery capacity for Fortune 500 clients moving beyond AI pilots, while the recent adoption of MLOps tooling indicates a shift toward operational rigor in model lifecycle management.
Tech Stack 48 technologies
Core StackPython Kotlin Java Swift AWS Flutter React Native Snowflake Databricks Salesforce Apex Terraform Docker Kubernetes Linux Kafka Android iOS Objective-C Google Maps Mapbox OpenLayers Azure GCP Git SQL Lightning Web Components Visualforce SOQL Oracle Cloud+17 more
AdoptingMLOps
What Giggso Is Building
◆Challenges
- Resource allocation impacts
- Cost management
- Outage prediction measurement
- Ad testing efficiency
- Audit and security compliance for model risk management
- Managing complex ai/ml systems
- Improving outage prediction accuracy
- Scaling model deployment
- Performance issues
- Critical bugs
▲Active Projects
- Outage prediction modeling
- Resource allocation forecasting
- Ad testing methodology enhancement
- Infrastructure as code implementation
- Ci workflow automation
- Linux system administration
- Complex integrations with external systems
- Data migration and cleansing
- Ci/cd pipeline implementation
- Ai/ml model deployment
Hiring Activity
15 roles · 2 in 30d
Department
Seniority
Company intelligence
