AIC Labs

A playground for experimental intelligence

Labs is where we prototype agentic patterns, AI search optimization, and human-augmented intelligence experiences. Work here is R&D: exploratory, measurable, and designed with human oversight. The best ideas become blueprints for production.

Mission

Build, learn, and release responsibly

AIC Labs explores agentic frameworks using Google ADK and AWS Strands, AI search optimization techniques, and orchestration blueprints that position AI as a companion to augment human intelligence. Every experiment pairs governance, observability, and human-centered UX.

The most powerful systems anticipate needs and act with measurable guardrails and human oversight.Malek Ould-Oulhadj, Founder & Principal Engineer
True innovation happens when art meets intelligence, when creativity meets code, and when vision meets execution.Malek Ould-Oulhadj

Focus Areas

Where we push intelligent systems forward

From AI search optimization to agentic orchestration frameworks, we explore the edges of what intelligent systems can responsibly deliver as companions to augment human intelligence.

Agentic AI Systems

Agentic workflows designed with human oversight. We combine planning, tool use, and memory with measurable guardrails for dependable multi-step execution.

Core capabilities

  • Context-aware planning and decomposition
  • Tool use across APIs, databases, and SaaS
  • Self-checks and recovery loops
  • Goal tracking with observability hooks
  • Human-in-the-loop controls

Technology stack

Google ADKAWS StrandsModel Context ProtocolOpenAPICustom Orchestration

Use cases

  • Customer support workflows with action-taking
  • Data analysis and reporting pipelines
  • Ops automations with safe-guards
  • Personalized recommendations and curation
  • Research assistants for synthesis

AI Search Optimization & Semantic Discovery

Advanced search systems that understand user intent through semantic embeddings, vector similarity, and intelligent ranking. We build AI-discoverable knowledge graphs with voice-enabled search that make your content accessible to both humans and AI assistants.

Core capabilities

  • Semantic search with neural embeddings
  • Voice search with real-time audio transcription
  • AI-native content discovery (ai-context.json, MCP)
  • Hybrid search combining embeddings and keywords
  • Multi-factor relevance scoring and ranking
  • Real-time query understanding and intent detection
  • Machine-readable knowledge graphs

Technology stack

Neural EmbeddingsVector SearchAudio TranscriptionVoice Activity DetectionModel Context ProtocolOpenAPIJSON-LD & Schema.orgNext.js API Routes

Use cases

  • Intelligent content discovery for websites
  • Voice-enabled search interfaces
  • AI assistant integration and discoverability
  • Natural language search interfaces
  • Knowledge base semantic search
  • Product and service discovery systems
  • Research and documentation search

Current Experiments

Ideas in active exploration

These are the prototypes and research threads currently on the Lab bench. Some become products, others become lessons.

Multi-agent collaboration

Systems where multiple specialized agents coordinate to solve problems no single model can handle.

Agentic code generation

Agents that write, test, and deploy code with built-in self-correction and governance.

AI-powered content pipelines

End-to-end pipelines that ideate, review, optimize, and publish content across channels automatically.

Intelligent document processing

Understanding, extracting, and acting on information from unstructured documents with human-level comprehension.

Conversational UI/UX design

AI-driven design tools that craft intuitive interfaces via natural language directives.

Collaborate

Bring your most ambitious idea to Labs

Interested in co-building AI search optimization, semantic discovery systems, or bringing agentic intelligence into your product as a human augmentation companion? We're ready to prototype boldly and land precisely.