ni7labs

Expertise

From research rigor to production-grade AI systems.

From ISO 42001 certification and agentic platforms to conversational access over enterprise data, forecasting for critical infrastructure, cloud-ready architectures, professional training and executive sessions, and evidence reviews (systematic surveys, bibliometrics)—grounded in regulated-industry delivery, PhD-level research, and hands-on leadership from architecture to production.

ISO 42001 & AI Management Systems

  • End-to-end AIMS implementation as Lead Implementer: governance frameworks, policies, and operating models for responsible AI.
  • Gap analysis against ISO 42001, remediation roadmaps, and audit-ready evidence portfolios.
  • AI-specific risk management: bias, transparency, accountability, and continuous improvement cycles post-certification.
  • Cross-functional coordination across technical, legal, compliance, and operations—experience includes utility-scale, regulated environments.

Agentic AI & Multi-Agent Platforms

  • Architecture of coordinated autonomous agents (ingestion, feature engineering, training, prediction, alerting, root-cause analysis, scheduling, monitoring).
  • Agent orchestration for operational forecasting and maintenance prioritization—ensemble models, risk scoring, and feedback-driven retraining.
  • Collaboration with digital factories and platform teams to align agent capabilities with production SLAs and observability.
  • NVIDIA-certified patterns for enterprise-grade autonomous workflows (NCP-AAI).

Conversational AI, RAG & Enterprise Data

  • Multi-agent conversational interfaces over SQL/NoSQL, documents, and warehouses—query understanding, routing, retrieval, and analysis agents.
  • LLM + RAG + semantic search with vector similarity, multi-turn context, and persona-aware summaries and visualizations.
  • Security Guardian–style controls: permissions, access validation, masking, and policy-aligned data governance for self-service analytics.
  • Production rollout paths for selected user groups, with iterative tuning from business and executive feedback.

Applied ML, Forecasting & Operations Analytics

  • Peak demand and utilization forecasting: time-series and ML over historical operating data, seasonality, weather or environmental drivers, and usage patterns.
  • Disruption and continuity risk forecasting by combining telemetry, maintenance logs, asset health, and incident history—dashboards and alerting for operations centers.
  • Model validation, monitoring, and operational handover—Power BI and reporting layers for predicted vs. actuals.
  • Impact focus: reliability, capacity planning, maintenance optimization, and fewer unplanned events.

Cloud, Hybrid & Platform Engineering

  • Azure-first delivery (App Services, Functions, ML, Storage, Cosmos DB, Cognitive Services) with AWS and GCP literacy.
  • On-premises to cloud migration, secure landing zones, and containerized workloads where appropriate.
  • Observability: Application Insights, Azure Monitor, and proactive reliability practices.
  • Program-level oversight of SAP S/4 HANA rollouts and alignment between ERP and modern data/AI platforms.

Solution Architecture, SDLC & Delivery Leadership

  • Full-stack ownership from requirements and architecture through deployment—.NET Core, Java ecosystems, and integration-heavy landscapes.
  • Performance engineering, security and coding standards, and vendor coordination for complex, regulated programs.
  • Proven across financial services (e.g., capital markets platforms), higher-education transformation, and large-scale utilities AI.
  • CTO- and director-level experience building roadmaps, mentoring teams, and aligning technology with institutional or enterprise strategy.

Training, Workshops & Executive Enablement

  • Professional training programs on AI/ML, generative AI, solution architecture, cloud platforms, and responsible AI—tailored for engineering, data, and leadership audiences.
  • Workshops and hands-on labs (e.g., agentic patterns, RAG, governance checkpoints) aligned to your stack and compliance context.
  • Executive briefings and board-ready sessions on AI strategy, ISO 42001 readiness, and technology roadmaps.
  • Academic-style depth where it helps: graduate-level teaching experience, thesis supervision, and faculty enablement on digital and AI topics.

Research Synthesis, Surveys & Evidence Reviews

  • Systematic and mapping literature reviews, research questions, inclusion criteria, quality appraisal, and synthesis reporting for software engineering, AI/ML, and adjacent fields.
  • Technology landscape surveys, trend analysis, and bibliometric or text-mining studies over scholarly or patent corpora—useful for R&D and vendor shortlists.
  • Study design for surveys and empirical evaluations; alignment with publication, grant, or internal evidence standards.
  • Advisory on research strategy, thesis direction, and peer-review readiness for universities and innovation teams (see The Labs · Research case study).

Ready to align architecture, agents, and assurance?

Start a conversation