abeebaRun AI on infrastructure you own.
Abeeba designs, deploys and operates private LLMs, GPU clusters and MLOps pipelines for companies whose data can't leave the building and whose GPU bills can't keep doubling.
Built for teams that can't send their data to someone else's model
Everything between your data and a model in production.
Seven services that cover the full lifecycle: where models run, what they cost, how they ship, and how they stay safe.
Private & On-Prem LLM Deployment
Run open-weight models inside your own servers, VPC or air-gapped network.
Learn moreGPU Infrastructure Optimization
Cut inference and training cost by raising utilization across your GPU fleet.
Learn moreCloud-to-AI Migration
Move legacy workloads and data onto AI-ready infrastructure without downtime.
Learn moreMLOps Pipeline Setup
Automate training, evaluation, deployment and monitoring end to end.
Learn moreCustom Model Fine-Tuning
Train models on your own data so they speak your domain and follow your rules.
Learn moreAI Security & Compliance Audit
Find model risks, data leaks and compliance gaps before an auditor or attacker does.
Learn moreOngoing Managed AI Support
We monitor, patch and improve your AI infrastructure on a monthly retainer.
Learn moreNot sure where to start?
Begin with a two-week Infrastructure Assessment. We map your workloads, costs and risks, then recommend a plan.
Book an assessment
Your models. Your hardware. Your rules.
Public AI APIs are a fast start and an expensive, risky place to stay. Running open-weight models on your own infrastructure changes the economics and the risk profile.
- Data stays inside your boundary. No prompts or documents sent to third-party model providers.
- Predictable cost. Pay for capacity you control instead of per-token prices that rise with usage.
- No lock-in. Open models, open-source serving and infrastructure as code in your repositories.
- Audit-ready. SSO, role-based access and logs for every request from day one.
From first call to a model in production.
Assess
We map workloads, data sensitivity, costs and risks, then recommend a target architecture.
Design
Capacity plan, security model and bill of materials, reviewed with your engineers.
Deploy
Infrastructure as code, serving stack, gateway and monitoring go live in stages.
Operate
We hand over with training, or keep running it under a managed plan.
Start from the problem you need solved.
Enterprise Cost Reduction
AI usage grows faster than budgets. We find where your GPU and API spend goes, then reduce it with better serving, scheduling and model choices,…
→Regulated Industries
Banks, hospitals and law firms can't send customer data to a public AI API. We build private AI platforms that keep data inside your boundary and…
→Scaling AI Startups
When usage takes off, the prototype stack breaks: latency spikes, API bills explode and margins disappear. We help AI-first startups move to…
→Legacy System Modernization
Your most valuable data often lives in the oldest systems. We modernize the platforms around it so AI can use that data safely, while the core…
→Multi-Cloud AI Strategy
GPU prices and availability change month to month across providers. A deliberate multi-cloud strategy lets you place workloads where they run best…
→What an engagement looks like.
Walkthroughs of typical projects: the starting point, the steps and what gets delivered.
Private LLM for underwriting analysts
Replace a public AI tool with a private model inside the lender's VPC, connected to credit policy documents with full audit logging.
Read the walkthrough
Cutting inference cost per patient summary
Profile GPU usage, introduce batching and a fine-tuned smaller model, and add chargeback dashboards per product line.
Read the walkthrough
From spreadsheets to an MLOps platform
Move demand forecasting models from notebooks to versioned pipelines with automated retraining and drift alerts.
Read the walkthroughBuilt for sectors where data can't leak.
Finance & Fintech
Private AI for banks, lenders and payment companies.
ExploreHealthcare & Life Sciences
HIPAA-aligned AI for providers, payers and research.
ExploreManufacturing & Logistics
AI at the plant, in the warehouse and across the supply chain.
ExploreRetail & E-commerce
Enterprise-scale AI for search, content and service.
ExploreLegal & Professional Services
Confidential AI for law, audit and advisory firms.
Explore Coming soonGovernment & Public Sector
Sovereign AI infrastructure for public bodies. Coming soon.
ExploreTeams that need AI to be private, fast and affordable.
Mid-to-large enterprises
You need AI in production but have no in-house AI infrastructure team.
AI-first startups
You are scaling fast and GPU or API costs are eating your margins.
Regulated industries
Finance, healthcare and legal teams whose data can't go to a public cloud model.
PE & VC firms
You want an independent audit of AI strategy and spend across portfolio companies.
Security is the product, not an add-on.
We work inside your environment under least-privilege access, document every change, and never move your data to our systems. Our Trust Center shows exactly where our own compliance program stands.
Ready to run AI on your own terms?
Book a 30-minute consultation with an infrastructure engineer. You'll leave with a clear view of options, costs and next steps, whether or not you work with us.