Secure AI for
|
We build custom AI agents and automation workflows. Founded on enterprise grade security and integrated seamlessly into your existing systems.
Security reference points
Practices applied to the engagement, not certification claims
Our Expertise
Startup friendly pricing, built on enterprise-grade security.
AI & Automation
Custom AI agents, machine learning models, and intelligent automation solutions tailored to your infrastructure. From private local LLMs to advanced multi agent workflows.
Security by Design
Built by ethical hackers. Every solution sits on a foundation of enterprise grade security to protect your data, ensuring your AI is resilient against modern threats.
Seamless Integration
We build high performance, scalable backends that integrate your custom AI solutions directly into your existing ecosystem, regardless of your current tech stack.
The difference is in the architecture
A demo is easy. A dependable system takes discipline.
We make the control surface visible before the first release, so security, reliability, and ownership are part of the build plan.
Standard AI wrapper
Fragile by default
- Raw prompts exposed to injection
- Unrestricted third-party data flow
- Single-path failures with limited observability
- Unverified outputs reaching downstream systems
- Broad credentials and unclear ownership
RelegoAI architecture
Hardened for operation
- Multi-stage guardrails and input boundaries
- Private inference or zero-retention provider paths
- Observable, resilient services with clear failure modes
- Scoped verification and output auditing
- Least-privilege access with explicit session boundaries
How We Work
A transparent, milestone driven process from first conversation to production deployment.
Discovery Call
A free 30 minute call where we map your challenge, goals, and constraints. No pitch just a focused conversation to determine whether we are the right fit.
Free · No obligationArchitecture & Threat Modelling
Before a single line of code, we design the solution and map its attack surface. Security is baked in from day one not added as an afterthought.
1–3 days · Fixed scopeBuild & Iterate
Rapid, milestone driven development with weekly check ins. You see real progress every week not a big reveal six months later.
2–12 weeks · Milestone billingHandover & Support
Full documentation, recorded walkthroughs, and a handover session with your team. Optional retainer for monitoring, updates, and future iterations.
Docs + training includedRecent Projects
A showcase of our deployed solutions, where cutting edge AI automation meets enterprise grade security.
MKU Support Hub: RAG Powered AI Chat & Knowledge Management Platform
A full stack, RAG powered student support platform featuring guardrailed AI chat, session scoped document analysis, and a secure admin verification, audit, and knowledge rollback dashboard.
SecureOps AI Autonomous Security Orchestration Platform
SecureOps AI is a production ready multi agent security orchestration platform that automates repository and container scans, triages findings via agent workflows, enforces policy decisions with OPA, and produces SARIF reports and actionable alerts.
Kalyzer - Advanced Security Assessment Tool
Introducing Kalyzer Advanced Security Assessment Tool 15 second comprehensive system analysis 27+ credential types with risk assessment Privilege escalation vector detection Network topology & service enumeration Professional reports with risk prioritization
Before we build
The questions worth answering early.
How do you keep sensitive data out of public AI models?
We define data boundaries before implementation. Depending on the risk profile, that can mean redaction, scoped credentials, private inference, self hosted models, or a zero data retention provider configuration.
Can you work with our existing stack?
Yes. We integrate with existing APIs, event systems, identity providers, and databases. The goal is a controlled capability that fits your architecture, not a rewrite that creates another isolated platform.
How quickly can we get a useful first release?
Most engagements begin with a focused discovery and threat-modelling phase, followed by a milestone-based build. A first production-shaped workflow is typically scoped within weeks, with timing depending on integrations and data readiness.
What happens after launch?
You receive documentation, a handover session, and an explicit operating model. Ongoing support is available for monitoring, security updates, model changes, and the next set of workflow improvements.