Headquarters
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End-to-end technology services engineered for scale, from specialized engineering talent on demand to production AI and custom software delivery.
End-to-end technology services engineered for scale, from specialized engineering talent on demand to production AI and custom software delivery.
The hardest gap in AI. Your demo works; your production system doesn't. We help teams move AI prototypes and early MVPs into reliable production systems by solving the challenges that usually appear after the demo: reliability, evaluation, cost, latency, security, deployment, and monitoring.
AI prototypes can perform well in controlled demos but break down when real users, production traffic, larger datasets, and enterprise requirements are introduced. Our consultants identify and address the technical gaps between an AI prototype and a production-ready system — from model evaluation and reliability to infrastructure, performance, security, and operational monitoring.
How our senior technology consultants guide your team from initial audit to production handover.
We evaluate your AI application architecture, model integrations, prompts, data pipelines, APIs, cloud infrastructure, security controls, secrets management, and failure handling to identify production-critical gaps.
We establish evaluation criteria, test datasets, quality benchmarks, regression tests, and failure scenarios to measure AI output quality and system reliability before production deployment.
We analyze model selection, token usage, inference patterns, API calls, database queries, caching, and infrastructure utilization to reduce operating costs and improve response times.
We design the production deployment architecture and establish CI/CD, logging, tracing, monitoring, alerting, and incident-response processes required to operate the AI system reliably at scale.
Choose the advisory structure that matches your current momentum. Fixed scopes, transparent pricing, and zero open-ended billing meters.
Leadership alignment, feasibility scoring, and high-level architecture roadmap before committing team resources.
In-depth system design, code repository audits, LLM eval benchmark harnesses, or unblocking complex roadmap features.
Fractional Head of AI or CTO advisory, continuous architecture reviews, vendor evaluations, and board technical oversight.
Direct strategic leadership from engineers who have shipped autonomous systems to production under stringent enterprise SLAs.
Leading enterprise AI strategy, system architecture, and autonomous platform development at Neno Technology. Over a decade of deep technical experience engineering high-scale distributed backends, low-latency telephony infrastructure (<200ms), and multi-agent production swarms.
“We advise from active production codebases, not theoretical slide decks. Every recommendation we give is grounded in architectures we have personally shipped, hardened, and benchmarked under live enterprise traffic.”