Systems Foundation
Cloud environments, infrastructure design, security posture, reliability, observability, and the operating practices needed to keep core systems dependable.
Small IT and AI Engineering Practice
Aidron builds and operates practical IT systems for teams that need the work to hold up.
Aidron is a focused technology company for commercial teams that need cloud infrastructure, automation, systems integration, security-conscious delivery, and practical AI capabilities where they make sense.
LLMs and Claude Code are part of the toolkit for AI-heavy work: architecture exploration, multi-file implementation, testing, documentation, and iteration. The company is broader than AI, but AI is a real delivery capability, not a side experiment.
Why Aidron
A small company with a broad technical bench.
Aidron is not trying to look like a giant consultancy. The value is a sharper one: hands-on delivery across infrastructure, automation, integration, and AI, with enough operational discipline to make systems usable after launch.
Lead capabilities
Program-ready technology focus areas.
Aidron’s work usually sits in three connected lanes: the systems a company runs on, the automation that keeps work moving, and the AI capabilities that are useful enough to put into production.
Operational Automation
DevOps workflows, systems integration, internal tools, release processes, runbooks, and automation that reduces manual work and operational drift.
Applied AI Delivery
LLM applications, RAG systems, model routing, evaluation, AI-assisted engineering workflows, and production rollout when AI is the right tool.
Proof of work
Open-source systems that show the AI and platform range.
These projects lean heavily into LLMs, but they also show the broader skills Aidron brings to IT work: architecture, APIs, cloud deployment, infrastructure-as-code, observability, tests, evaluation, and operational tradeoffs.
RAG · Claude API · Evaluation
stratum
Production RAG Engine
Hybrid BM25 + dense retrieval, RRF fusion, cross-encoder reranking, citation-grounded generation with Claude, DeepEval gates, Streamlit UI, FastAPI service, and Terraform-backed AWS deployment.
Claude generation
Weaviate production store
Langfuse-ready tracing
LLM Platform · Routing · AWS
multi-llm-platform
Multi-LLM Inference Gateway
Production-grade gateway for routing across Anthropic, OpenAI, and AWS Bedrock with semantic caching, auth, rate limiting, CloudWatch observability, and Terraform-managed serverless infrastructure.
Model routing
Semantic cache design
Serverless deployment
Agents · DevSecOps · GitOps
gitops-sentinel
Autonomous Infrastructure Remediation
Confidence-gated AIOps workflow for Kubernetes that classifies incidents, plans remediations, routes to PR review or auto-apply, and validates outcomes through GitOps controls.
Human approval gates
Step Functions agents
Rollback-aware delivery
Fine-tuning · Governance · Eval
LLM-Specialization-Platform
Model Specialization Pipeline
QLoRA SFT, DPO preference optimization, artifact re-evaluation, null-case training, constrained decoding, GGUF export, and reproducibility manifests for task-specific LLM deployments.
SFT + DPO pipeline
Schema-bound outputs
Reproducible runs
How the work gets done
Claude Code is one part of a practical engineering workflow.
Aidron uses Claude Code when it helps move real work forward, especially on LLM-heavy systems and complex codebase changes. It supports the work; it does not replace engineering judgment, testing, or operating discipline.
Architecture discovery
Repository exploration, dependency mapping, interface review, and implementation planning before files are changed.
Multi-file implementation
Feature delivery, refactoring, infrastructure updates, test repair, and documentation in one connected workflow.
Toolchain execution
Shell commands, test suites, formatters, Terraform plans, Git workflows, and CI checks integrated into the build loop.
MCP-ready workflows
Patterns for connecting AI tooling to project context, docs, issue trackers, internal tools, and repeatable team workflows.
Review and governance
Human review gates, traceable decisions, evaluation checks, rollback paths, and documentation that supports adoption.
Services
IT delivery services with practical AI depth.
These services are designed for software companies, platform teams, operations-heavy businesses, and regulated commercial environments that need dependable systems, not just advisory notes.
Cloud and Infrastructure Modernization
Design and improve cloud environments, landing zones, network boundaries, deployment patterns, monitoring, and infrastructure-as-code.
DevOps and Automation
Build CI/CD pipelines, release workflows, environment automation, internal tools, and repeatable processes that reduce manual drift.
Systems Integration
Connect applications, APIs, data flows, and operational tools so teams can move information reliably across the business.
LLM and RAG Systems
Build LLM-powered applications, retrieval pipelines, knowledge systems, model gateways, and evaluation loops where AI is the right fit.
Cybersecurity and Control Support
Support access control, auditability, security review, documentation, runbooks, and operating procedures for high-accountability environments.
Technical Delivery Support
Help teams with architecture review, backlog execution, code modernization, documentation, handoff, and managed operational support.
Why Aidron
What we bring to a program.
Delivery-first execution
We stay focused on working systems, operational readiness, documentation, and handoff, not strategy artifacts that never become usable capability.
Infrastructure depth
Cloud, networks, automation, deployment patterns, and observability are treated as part of the same operating picture.
AI with operational discipline
LLMs are used where they help. Evaluation, access control, model behavior, and rollback paths are part of the build.
Documentation that survives handoff
Runbooks, SOPs, diagrams, control notes, and architecture records are written so another team can operate the system.
Security-aware implementation
Security review, auditability, access boundaries, and deployment repeatability are considered while the system is being built.
Focused team, senior attention
Aidron is built for technical work where judgment, accountability, and speed matter more than large-team ceremony.
Founder
Ade Daramola
Principal Engineer · Founder
Focus
AI platforms, cloud infrastructure, and autonomous systems
Infrastructure
15+ years AWS infrastructure experience
Selected work
GitOps Sentinel, Multi-LLM Platform, Stratum RAG
Style
IaC-managed, testable, observable, documented
Ade is an AI and cloud engineer focused on production-grade systems: cloud-native infrastructure, agentic workflows, RAG platforms, and multi-model orchestration. His public work shows the same operating style Aidron brings to clients: infrastructure-as-code first, observed, documented, and built for handoff.
The point of the founder-led model is accountability. The person shaping the architecture is close to the implementation, the tradeoffs, the tests, and the operational details that decide whether a system actually gets used.
Certifications and training
Ade holds certifications and advanced technical training across several disciplines, including AWS cloud infrastructure, NVIDIA agentic AI and large language model (LLM) systems, Terraform automation, cloud security, and production-grade AI engineering practices.
Private-sector focus
Where Aidron is positioned to help.
Software and Product Teams
Cloud platforms, code modernization, internal developer tools, product integrations, and AI features where useful.
Financial Services and Fintech
Secure infrastructure, document workflows, auditability, access control, automation, and evaluation-heavy AI deployments.
Healthcare and Life Sciences
Cloud architecture, integration work, knowledge retrieval, workflow support, and careful handling of sensitive operating contexts.
Operations-Heavy Businesses
Process automation, support tooling, internal systems, cloud reliability, and AI-assisted operational decision support.
Contact
Bring an infrastructure, automation, integration, or AI problem.
Bring a repo, workflow, cloud environment, or AI idea. Use the form to start a focused conversation; this static site opens a prepared email draft from your own email client.
Modernize infrastructure
Cloud environments, deployment patterns, observability, access boundaries, and support-ready handoff.
Build AI capability
RAG systems, LLM applications, model routing, evaluation, and AI-assisted engineering workflows.
Improve delivery and automation
DevOps, CI/CD, internal tools, system integration, process automation, and technical documentation.
Email: info@aidrontech.com