StoneBrite Solutions engineers agentic AI systems, LLM evaluation frameworks, and enterprise software for organisations that need AI to deliver real, measurable outcomes.
Powered by industry-leading AI & cloud platforms
End-to-end engineering services — from autonomous AI agents to enterprise software and cloud infrastructure.
Multi-agent architectures that autonomously plan, reason, and execute complex business workflows using the latest LLM frameworks.
Rigorous evaluation frameworks for LLM applications — adversarial testing, hallucination detection, and CI/CD quality gates.
Embed AI into your existing enterprise stack — custom LLM fine-tuning, vector databases, MLOps pipelines, and governance frameworks.
Production ML pipelines for demand forecasting, anomaly detection, churn prediction, and real-time business intelligence.
Full-stack engineering with AI at the core — scalable APIs, cloud-native microservices, and performant web applications.
Strategic technology guidance and managed IT support — from cloud architecture reviews to vendor selection and enterprise infrastructure planning.
Real AI systems built, deployed, and measured in production environments.
Enterprise multi-agent orchestration platform with a visual workflow builder. Supports ReAct, Plan-and-Execute, and custom agent topologies with full observability.
LLM testing framework with adversarial prompt generation, hallucination detection, and CI/CD-native quality gates. Integrates with GitHub Actions, GitLab, and Jenkins.
Real-time demand forecasting pipeline processing 2M+ daily events for a retail chain. 94% prediction accuracy with live anomaly alerting.
Autonomous code review agent enforcing security policies, detecting OWASP vulnerabilities, and generating fix suggestions — integrated into GitHub and Jira.
Document intelligence platform with multi-modal RAG. Processes contracts, reports, and technical docs — answering complex queries with cited sources.
Automated red-teaming toolkit for LLM safety evaluation — covering prompt injection, jailbreaks, data leakage, and toxicity with structured audit reports.
Most teams deploy AI features without a validation framework — then scramble when hallucinations or regressions reach production. We build the test infrastructure so your models behave correctly in every scenario.
500+ injection patterns, jailbreak attempts, and auto-generated edge cases against your production prompts.
RAGAS and TruLens benchmarks with custom metrics aligned to your specific use-case KPIs — tracked over time.
Block deployments when AI quality degrades. Native integrations with GitHub Actions, GitLab CI, and Jenkins.
Red-team reports, bias detection, PII leakage tests, and documentation aligned to EU AI Act and ISO 42001.
Our AI team stays current with the latest advances in agentic architectures, RAG, and model evaluation — applying academic rigour to real engineering problems.
Every system ships with observability, fallback handling, rate limiting, and SLAs built in. We build for real load, not demonstrations.
Every AI system we deliver includes an evaluation framework. You always have data on how your models are performing and why.
From architecture to deployment to monitoring — we own the outcome, not just the code. Your success is the deliverable.
