Your AI demo works. Your production system doesn't.
Your prototype took a weekend.
Production will take an engineer.
Agent engineering. Not agent scaffolding.
Featured Work
// WORK
HECCO — AI Companion for Wellness & Fitness
An AI companion that talks to you like a doctor. Real-time voice via WebRTC, wearable data sync, medical document analysis, and personalized health guidance. Multi-model routing across GPT-4o-mini, Gemini, and Azure Realtime. Evaluation pipeline scoring 10,000+ interactions daily.
500K+ lines. Both app stores. 5,000+ users. Zero hallucination on medical data. Exited.
Regulatory Compliance Engine
Regulatory documents turned into executable compliance logic. AI extracts once, humans review, then all decisions run as pure symbolic evaluation. Zero AI in the decision path. Deterministic, traceable, auditable.
Deterministic compliance verdicts. Zero hallucination. Full audit trail.
E-Commerce Operations Agent
An agent that encodes 30 years of manufacturing domain knowledge into automated marketplace operations. Product image generation, listing optimization across 4 platforms, catalog management, and pricing intelligence.
Catalog automation across 4 marketplaces. Domain expertise, not just data.
■KNOW WHAT YOU'RE BUYING
The 70% vs. The 100%.
Claude Code gets you a working demo. Here's what production actually requires.
// THE LINE
COMMODITY
This is free now. Claude Code does this. So does every freelancer on Upwork.
- −Working prototype from Claude Code in 2 hours
- −Chatbot that passes the first demo
- −RAG pipeline from a YouTube tutorial
- −n8n / Make / Zapier automations
- −Agent scaffolding that works on your laptop
- −The 70% that anyone can build
ENGINEERING
This is engineering. The part that breaks at scale. The part Claude Code can't do.
- +Security hardening (2.74x more vulns in AI-generated code)
- +Evaluation pipelines (not 'it looks right')
- +Domain knowledge architecture (not prompts — structured expertise)
- +Multi-model cost routing by task
- +Failure mode design (agents fail silently — ours don't)
- +The last 30% that takes 90% of the expertise
■ENGINEERING DEPTH
What Production Demands.
The engineering that separates a demo from a system your business depends on.
// ENGINEERING DEPTH
Evaluation Pipelines
Every agent we build ships with an evaluation pipeline. 10,000+ interactions scored and benchmarked daily on a healthcare platform we built. Not 'it looks right.' Not 'the client is happy.' Quantified, baselined, monitored.
Multi-Model Routing
Classification on GPT-4o-mini. Extraction on Gemini 2.5 Pro. Voice on Azure Realtime API. OCR on DeepSeek. One model for everything is lazy and expensive. We route each agent task to the right model at the right cost.
Domain Knowledge Architecture
An agent without domain knowledge is a chatbot. We structure years of expertise into queryable systems. Medical documents with 15 body system classifications. Legal bylaws with cross-reference graphs. Manufacturing specs with material hierarchies.
Agent Failure Modes
Agents fail silently. A healthcare agent that hallucinates kills trust. We build multi-agent validation chains, structured output schemas, fallback paths, and human escalation triggers. The failure mode design is the engineering.
Always-On Deployment
Your agent should work at 3am without you. Dedicated hardware or cloud infrastructure. Monitoring and observability. Cost tracking per interaction. Autonomous operation with guardrails.
How We Build Agents
// METHODOLOGY
Domain Mapping
We structure your domain expertise into a knowledge architecture. PDFs, tribal knowledge, spreadsheets, SOPs. Everything becomes structured, versioned, and queryable by your agent.
Agent Design
Architecture decisions: which models for which tasks. Tool design. Memory systems. Evaluation criteria BEFORE building. Planning and failure mode analysis. This is where 80% of the engineering happens.
Build + Evaluate
Agent development with continuous evaluation. Every capability tested against baselines. Multi-agent coordination if the job requires it. Not shipped until the evaluation pipeline is green.
Deploy + Improve
Production deployment on your infrastructure or ours. Monitoring, cost tracking, performance dashboards. Your agent gets smarter every week from real usage data. Always-on, always improving.
Your automations follow rules.
Our agents make decisions.
Anyone can build one agent. Engineering it to replace ten manual processes — that's the multiplier.
■SERVICES
What we build.
What you get.
// SERVICES
AI PRODUCTION HARDENING
You built it with Claude Code or Cursor. We make it production-ready. Security audit, evaluation pipeline, failure mode design, performance optimization. For teams that shipped the 70% and need an expert for the last 30%.
Your system ships production-ready: security hardened, evaluation pipeline running, 30 days of post-deploy support.
AUTOMATION-TO-AGENT MIGRATION
Your automations follow rules. RPA records clicks. Both break at edge cases. We replace them with API-native agents that connect directly to your systems, reason through exceptions, and never touch a screen. From Zapier/n8n/Make or UiPath/Automation Anywhere to intelligent agents.
Your automations replaced with API-native agents, evaluated against baselines, tuned for 30 days in production.
CUSTOM AI AGENT
One agent, one job function, engineered for production. Not a demo. The full system your business depends on. Domain knowledge encoded. Evaluation pipeline included. Failure modes handled. Monitoring built in.
One production agent — evaluated, monitored, documented. 60 days of tuning from real usage data.
MULTI-AGENT SYSTEM
Multiple agents coordinating across your business. Governance, compliance, audit trails. Dedicated infrastructure. For companies ready to replace entire workflows, not just tasks.
Coordinated agent system on dedicated infrastructure. Team trained. 90 days of hands-on support.
ONGOING AGENT SUPPORT
After we build, we stay. Agent maintenance, performance monitoring, new capability rollouts. Your agents get smarter every week. The hardest offering to commoditize, because it is a relationship built on your domain knowledge.
Weekly calls, continuous tuning, monitoring dashboards, priority support, and a roadmap that evolves with your business.
The Discipline
Agent engineering is a discipline. Evaluation. Architecture. Domain knowledge. Deployment. Maintenance. We practice all of it.
SEE HOW IT WORKS+■OUR PRODUCTS
We ship our own.
Our money. Our risk. Same engineering rigor. Real users.
NiftyX→
Our internal AI trading terminal. 8 autonomous agents, 15 markdown rule files, zero algorithmic code. A personal hedge fund desk running live on Indian markets. Built for one operator — not a product, not a service. Proprietary and research-only.
InternalE-Commerce / AI OperationsArtique AI→
AI-powered e-commerce operations. Automated product photography, catalog generation, and multi-marketplace listing optimization. 30 years of manufacturing domain knowledge encoded into the system.
ActivePersonal AI / Internalnyxa.life→
Our internal AI system that runs a full life operating system. Health tracking, career strategy, financial planning, relationship awareness. Context-aware across every domain. Built on Claude. This is how we stress-test our own methodology daily.
ActiveDeveloper Tools / AI EngineeringGodmode→
A spec-driven development harness built on top of Claude Code. 19 skills, 4 specialized agents, 9 lifecycle hooks. Turns Claude Code into a software factory — every product we build runs through it. Open source. Built because the default Claude Code workflow wasn't disciplined enough for production systems.
ActiveSalus
An AI voice wellness coach that lives on Telegram. Conversational, context-aware, and built for daily use. Voice input and output. Remembers context across sessions. Built on Claude with ElevenLabs voice. Shipping April 2026.
Coming SoonPocketClaw→
An open-source autonomous phone agent. On-device architecture — accessibility tree navigation, action sandboxing, natural language task execution. No server required. Privacy-first. The agent that executes tasks on your phone the way you would.
Research