Intelligent AI. Seamlessly Integrated.
We help you harness the power of AI safely. From custom LLM workflows to securing your machine learning pipelines, we make AI work for your infrastructure.
Custom LLM Workflows
Embed the latest foundation models into your products. We design the architecture to serve, scale, and orchestrate large language models reliably.
- RAG (Retrieval-Augmented Generation) Architecture
- LangChain & LlamaIndex integrations
- Vector Database deployment & scaling
- Model evaluation and prompt engineering workflows
AI Pipeline Security
Don't let your data become a training liability. We secure the entire ML lifecycle—from data ingestion to model inference.
- Prompt Injection & Jailbreak mitigations
- Data Privacy and PII anonymization
- RBAC for Vector Databases and AI endpoints
- Shadow AI auditing and governance
Intelligent Internal Tools
Supercharge your DevOps and Security teams with AI-driven automation that reduces toil and alert fatigue.
AI for DevSecOps
Automated code reviews, vulnerability triaging, and remediation suggestions integrated directly into GitHub/GitLab.
Incident Response Copilots
Custom bots that synthesize logs, correlate alerts, and draft incident reports so your on-call engineers can focus on fixing the issue.
Our AI Architecture Process
We don't just bolt on API calls. We build robust, secure, and measured AI systems.
Discovery & Threat Modeling
We evaluate your use case, data sources, and potential attack vectors before writing a single line of code.
Architecture & Implementation
Designing scalable RAG systems, integrating Vector databases, and orchestrating models through LangChain.
Evaluation & Governance
Deploying guardrails, implementing RBAC for data access, and setting up ongoing LLM evaluation.
Proven Use Cases
Real-world applications of our AI integration and security implementations.
Secure Support Copilot
Built a RAG-based AI assistant capable of answering customer queries against internal documentation. We implemented strict PII scrubbing algorithms and RBAC controls to ensure the LLM never ingested sensitive user data.
Automated Cloud Auditing
Deployed a custom internal LLM workflow to summarize infrastructure drifts and output actionable Terraform remediation code directly into developer pull requests, saving hundreds of hours of manual review.
Ready to Build with AI?
Let’s discuss how we can securely integrate LLMs and automation into your infrastructure.
No commitment required. Confidentiality guaranteed.