Capabilities

The reusable AI systems, design engineering philosophy, and platform capabilities behind Nara Labs products.

These are the technical foundations behind products like ReadyLead and ProbeIQ — for technical buyers, investors, recruiters, and engineering teams evaluating how we build applied AI systems.

AI Systems & Platform Capabilities

Reusable technical surfaces that power Nara Labs products — from agent workflows and retrieval to realtime interfaces and design engineering.

Agentic Systems

Building AI systems that can reason, plan, use tools, and maintain context across complex workflows.

Demonstrated in

AheadProbeIQLocal PM OS

Explored

Multi-step reasoningTool orchestrationMemory systemsWorkflow planningAgent evaluation

Retrieval Systems

Designing systems that retrieve, structure, and inject relevant knowledge into AI workflows.

Demonstrated in

ProbeIQLocal PM OS

Explored

RAG pipelinesSemantic searchContext injectionKnowledge retrievalDocument understanding

Realtime Voice

Building low-latency conversational systems for interactive reasoning and decision support.

Demonstrated in

AheadYC Voice AI Hackathon

Explored

Streaming responsesVoice interactionsStateful conversationsRealtime decision supportMultimodal interaction patterns

Reasoning Systems

Building systems that help users compare options, simulate scenarios, and make better decisions.

Demonstrated in

AheadProbeIQ

Explored

Scenario comparisonTradeoff analysisDecision simulationStructured outputsExplainable recommendations

Local AI

Exploring on-device agents and private AI workflows that can run close to user or company data.

Demonstrated in

Local PM OSDell × NVIDIA Local AI Hackathon

Explored

Local inferencePrivate workflowsOn-device agentsLocal knowledge basesEdge AI constraints

Design Engineering

Combining product design, frontend implementation, and AI-native interaction systems.

Demonstrated in

AheadNara Labs websiteLocal PM OS

Explored

Rapid prototypingProduct architectureAI-native UXDesign systemsFrontend implementation

Context Engineering

Designing memory, retrieval, structured inputs, and knowledge layers that make AI systems more useful.

Demonstrated in

AheadProbeIQLocal PM OS

Explored

Memory designStructured contextPrompt architectureKnowledge layersUser state modeling

Agent Evaluation

Testing and validating AI workflows so systems become more reliable, useful, and safe.

Demonstrated in

AheadHackathon projects

Explored

Scenario testingPrompt evaluationHuman feedback loopsWorkflow validationReliability checks

Multi-Agent Systems

Coordinating specialized agents across workflows with clear responsibilities and shared context.

Demonstrated in

Local PM OS

Explored

Agent routingRole-specific agentsShared contextWorkflow orchestrationTask decomposition

Agent Governance

Exploring controls, permissions, and review loops that make agent behavior safer and more trustworthy.

Demonstrated in

Local PM OSHackathon projects

Explored

Human-in-the-loop reviewGuardrailsApproval workflowsPermission boundariesAgent behavior constraints

Systems We've Built

How our projects map to concrete AI capabilities.

Memory Systems

Ahead, ProbeIQ, Local PM OS

Retrieval & RAG

ProbeIQ, Local PM OS

Agent Workflows

ProbeIQ, Local PM OS

Realtime Voice

Ahead, YC Voice AI Hackathon

Decision Simulation

Ahead

Local AI

Local PM OS, Dell × NVIDIA Local AI Hackathon

Context Engineering

Ahead, ProbeIQ, Local PM OS

Agent Evaluation

Ahead, Hackathon projects

Multi-Agent Coordination

Local PM OS

Human-in-the-Loop

Ahead, Local PM OS

Capability Maturity

A transparent view of where we are actively building, exploring, and researching.

Active
  • Agentic Systems
  • Realtime Voice
  • Reasoning Systems
  • Design Engineering
  • Context Engineering
Exploring
  • Retrieval Systems
  • Local AI
  • Multi-Agent Systems
  • Agent Evaluation
Researching
  • Agent Governance
  • Monitoring / Observability
  • Production Reliability
  • Safety & Permissioning

Current Stack

The tools and technical layers we use to prototype and ship applied AI systems.

Models

  • OpenAI
  • Claude
  • Gemini
  • Nemotron

Agent / AI Frameworks

  • OpenAI SDK
  • Vercel AI SDK
  • LangGraph
  • LangChain

Retrieval

  • RAG pipelines
  • Vector search
  • Embeddings
  • Structured context

Frontend

  • Next.js
  • React
  • TypeScript
  • Tailwind CSS

Infrastructure

  • Vercel
  • Supabase
  • PostgreSQL
  • GitHub

Interfaces

  • Chat
  • Voice
  • Web applications
  • Decision cards
  • Dashboards

Project Evidence

Where these capabilities show up in shipped projects and prototypes.

Ahead

Conversational decision engine for financial and life decisions.

Realtime voiceMemory systemsDecision simulationScenario comparisonAI-native interaction design
View project →

ProbeIQ

Agentic research and learning platform for retrieval, reasoning, and interactive exploration.

RAGKnowledge retrievalAgentic research workflowsContext engineeringStructured reasoning
View project →

Local PM OS

AI-native product management operating system for turning conversations, documents, and project context into workflows.

Agent workflowsMulti-agent coordinationLocal AIContext routingHuman-in-the-loop workflows
View project →