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AI engineering for real workflows.

We help teams build, connect, and operate AI systems with clear architecture, working code, and practical handoff.

psychology
01

AI Product Development

Custom AI products built for your business. LLM integration, RAG pipelines, intelligent agents, and production-ready inference.

  • Multi-model orchestration (Claude, GPT, Gemini, local)
  • Retrieval-augmented generation with vector DBs
  • Agentic workflows with tool calling
  • Fine-tuning and domain adaptation
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memory
02

Edge AI, Local & Open Models

Run models where the data lives. Open-weight LLMs served locally, small models tuned for specific tasks, and edge deployment on NVIDIA hardware — no data leaves the box.

  • Local LLMs — Ollama, llama.cpp, vLLM, LM Studio for private inference
  • Open models — Llama, Gemma, Mistral, Qwen, Phi, Nemotron
  • Small models for edge — 1B–8B quantized, specialized for your task
  • Edge hardware — Jetson AGX Orin, GB10, DGX Spark
  • Optimization — TensorRT FP16/INT8, DeepStream, NIM microservices
Ollamallama.cppLlamaGemmaMistralQwenJetsonTensorRT
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architecture
03

AI Platform Design

Secure AI platforms with model routing, data boundaries, observability, and clear operating rules.

  • Multi-tenant isolation and data residency
  • MLOps / LLMOps and observability
  • Cost, latency, and reliability SLOs
  • Security, red-teaming, and audit trails
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04

AI Setup & Enablement

Get your team productive with AI. Claude Code, Copilot, ChatGPT Enterprise, and custom workflows — installed, trained, with playbooks.

ClaudeCopilotWorkflowsTraining
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05

Full-Stack Engineering

Web apps, internal tools, integrations, and extensions built with clean handoff and practical deployment paths.

Next.jsReactSupabaseVercel
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06

Startup Advisory

Fractional CTO / technical advisor for early-stage startups. Architecture, hiring, go-to-market, and fundraising support.

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A practical path from question to working system.

Clear scope, steady demos, and handoff your team can keep using.

01

Discovery

We map the problem, technical landscape, and goals.

02

Architecture

System design, tech stack, data flow, deployment strategy. Clear plan, your approval.

03

Build

Working increments, reviewable code, and deployments when the path is ready.

04

Support

Monitoring, iteration, knowledge transfer, and ongoing partnership.

Have an AI project in mind?

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