Case Studies in AI & Cloud Excellence
Discover how Infracta™ has achieved transformative results in AI systems, cloud infrastructure, and enterprise operations — delivering measurable value with strategic impact.
We’ve delivered high-impact AI systems across various sectors. Full case study breakdowns will be available soon.
Real-World Results. Quantifiable Value.
With over twenty years of experience, we have helped teams launch, scale, and manage essential AI infrastructure projects. These anonymized case studies demonstrate how complex systems can become secure, auditable solutions — delivered on time and within governance.
100M
+
In annual risk mitigated
60
%
Faster LLM onboarding across 4 enterprise teams
300+
Engineers enabled across AI governance programs
5
Global sectors supported (public, finance, legal, health, tech)
Every case below was delivered by multidisciplinary teams at Infracta™, including infrastructure architects, ML strategists, DevSecOps engineers, and compliance leads. These are real, repeatable, and quantifiable results — for clients who don’t have time for AI experiments, only outcomes.
Secure, Compliant LLM Platform (U.S. Government Agency)
Measure
- ↓ 60% onboarding time (4 weeks → under 10 days)
- ↓ 52% infra cost per project ($180K → $85K)
- ↑ 100% audit compliance (FedRAMP + token-level traceability)
- $3M+ projected annual savings
Outcome
Became the blueprint for multi-agency GenAI deployment.
[Case Study Details Coming Soon]
[Case Study Details Coming Soon]
AI-Powered Document Classification (Federal Regulator)
Measure
- ↓ Review latency: 5–6 days → 2–3 days
- ↓ Search latency: 20s → <5s
- ↑ 40% clustering accuracy & traceability
- 100K+ docs enriched/day
Outcome
Over 50GB of unstructured data processed daily
GenAI Infrastructure Rollout (Enterprise Platform)
Measure
- ↓ 75% onboarding time
- ↑ 99.9% uptime across 4+ depts
- 25+ modular templates
Outcome
Standardized GenAI delivery in high-compliance org
[Case Study Details Coming Soon]
[Case Study Details Coming Soon]
Predictive AI for Retention (National Workforce Program)
Measure
- ↑ 80%+ early ID of attrition risk
- ↓ 17% attrition in pilot unit
- 200+ managers trained
Outcome
Real-time alerts for over 300,000 employees
Secure Microservices Stack (AI Enablement Group)
Measure
- ↓ Duplication by 60%
- ↓ Time to prod: 4–6 weeks → <2 weeks
- ↓ Support tickets by 70%
Outcome
Shared stack adopted organization-wide for LLM access
[Case Study Details Coming Soon]
[Case Study Details Coming Soon]
Cloud Cost Optimization (Fortune 500 Division)
Measure
- ↓ AWS overages: 25–30% → <10%
- ↑ Audit governance score 3x
- 40+ architecture docs
Outcome
Over $3M in annual savings through standardized governance.
CI/CD Infrastructure for LLMs (DevSecOps Program)
Measure
- ↓ Rollback time: hours → minutes
- ↑ SLA compliance: 99.9% uptime
Outcome
Default pipeline for over 5 AI product lines
[Case Study Details Coming Soon]
[Case Study Details Coming Soon]
Multi-Agency CFR Toolkit (Cross-Agency AI Program)
Measure
- ↑ Rollback parity: 100% across 4+ agencies
- ↓ Coordination time: 2+ weeks → ~5–6 days
Outcome
Explainability and transparency on a federal scale