AI / ML Services by ELMNTX

Every Model. Every Scale.
Governed Lake to Edge.

ELMNTX moves enterprises from AI experimentation to production-grade impact — with vendor-agnostic advisory, hands-on implementation, and MLOps governance across every AI discipline.

UAE · KSA · India · UK3 Proprietary Products
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AI Disciplines
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Proprietary Products
Complete Discipline Coverage

Not Just LLMs — Full-Spectrum AI

From generative AI to edge inference, we cover every layer of the modern AI stack with production-grade delivery and measurable outcomes.

🤖

Generative AI

RAG architectures, fine-tuning (Llama 3, Mistral, GPT-4, Claude), multi-modal GenAI, safety guardrails, PII redaction, and hallucination detection.

RAGFine-tuningGuardrailsMulti-modal
📈

Machine Learning

Predictive & prescriptive ML — demand forecasting, churn, uplift modeling. Responsible AI with SHAP/LIME explainability and legacy SAS/R modernization.

ForecastingXGBoostAutoMLBias Audits
👁️

Computer Vision

Defect detection, medical imaging, retail shelf analytics, CCTV anomaly detection. YOLOv8, SAM, ViT, DeepSORT — from labeling to edge inference.

YOLOEdge CVVideo AnalyticsActive Learning
💬

NLP

Information extraction, multilingual NLP, document understanding (LayoutLM), sentiment & emotion detection, legal and medical text analytics.

NERmT5/mBERTLayoutLMHugging Face
⚙️

LLM & MLOps

LLM selection, orchestration & routing. CI/CD for ML, canary deployments, prompt tracing, token cost tracking, and drift detection with LangSmith / Arize.

MLflowDVCLangSmithArize
🎯

Reinforcement Learning

Dynamic pricing, inventory optimization, multi-agent fleet coordination. Sim2Real advisory: train in Unity / NVIDIA Isaac, deploy to real environments.

Ray RLlibSim2RealMulti-Agent
🔗

Graph Machine Learning

Knowledge graphs, fraud ring detection via GNNs, supply chain risk modeling, anti-money laundering. Graph RAG for enhanced retrieval pipelines.

PyGNeo4j GDSKnowledge Graph
📡

Time Series & Anomaly

Demand, energy, and IoT telemetry forecasting with Prophet, DeepAR, TFT. Real-time anomaly detection with autoencoders and causal ML root-cause analysis.

TFTN-BEATSIsolation Forest
🔬

Recommendation Systems

Two-tower neural recsys, session-based GNNs, contextual bandits, real-time vector search with Milvus / Qdrant, and online A/B interleaving evaluation.

Two-TowerFeastQdrant

Edge AI & TinyML

Quantization (INT8), pruning, distillation for MCUs and Raspberry Pi. Federated learning across edge devices — healthcare, mobile, and IoT without data centralization.

TF LiteNVIDIA JetsonFederated ML
🛡️

Explainable AI & Safety

SHAP, LIME, counterfactuals, adversarial testing (Foolbox / CleverHans), Constitutional AI alignment layers, and interpretable model alternatives like GAMs.

SHAPLIMEAdversarial Testing
🧪

Synthetic Data

CTGAN/TVAE for tabular privacy, StyleGAN & diffusion for rare defect image generation, LLM-augmented text augmentation and time-series GANs for sensor data.

CTGANDiffusionPrivacy-Preserving
The Foundation

Data Engineering for AI-Ready Infrastructure

"Garbage in, GenAI garbage out." We ensure your data is reliable, fresh, and governed before a single model is trained.

01

Self-Service BI & Governance

  • Semantic layer & metrics store (dbt + MetricFlow)
  • Data Mesh — domain-owned data products
  • Data catalog & lineage (OpenMetadata, Atlan)
  • Column-level security via Snowflake RBAC / Databricks UC
02

Data Warehouse & Lakehouse

  • Lakehouse strategy on Delta Lake, Iceberg, or Hudi
  • Modernization from Teradata/Netezza to Snowflake/BigQuery
  • Lambda/Kappa real-time + batch (Kafka → Flink → Iceberg)
  • Cost governance — query tagging, auto-suspend, pruning
03

Big Data Engineering

  • Streaming pipelines: Kafka/Pulsar + Flink/Spark Streaming
  • Scalable ETL/ELT: dbt, Airflow, Prefect, Dagster
  • CSV/JSON → Parquet/ORC with ZSTD/Snappy compression
  • Data quality with Great Expectations / Soda auto-alerts
04

Vector & Feature Infrastructure

  • Embedding pipelines: text, image, multimodal
  • Vector stores: FAISS, Milvus, Pinecone, LanceDB
  • Online/offline feature stores (Feast, Tecton)
  • Real-time features for CV, recsys, and forecasting
Enterprise AI Platform

AI-BOX — Secure. On-Prem. Agentic.

A turnkey enterprise AI platform that transforms organizations with next-generation AI agents — without exposing a single byte to public models.

Challenge
AI-BOX Resolution
⚠ Sensitive data exposure to public AI✓ All processing inside your own servers
⚠ No AI-specific security controls✓ Prompt injection detection + output sanitization
⚠ GDPR & data residency compliance✓ Full audit logs + role-based agent access
⚠ Agent over-permission risks✓ Granular just-in-time access per task
⚠ No continuous AI monitoring✓ Real-time dashboard of every agent action
⚠ Vendor lock-in on rules & pricing✓ Own your entire AI stack — no dependency
Architecture Stack

Bare metal / VMware / Kubernetes → Data lake / SharePoint → Zero-trust TLS 1.3 → Llama / Mistral + fine-tuned models → REST / event hooks to ERP/CRM → Role-specific AI agents → Unified SSO + audit engine.

Deployment Strategy — 3 Phases
Phase 1
🚀
Pilot — Quick Wins
Deploy 2–3 agents (e.g. Expense Management + Meeting Assistant) for one department. Measure ROI in 4 weeks.
Phase 2
📈
Scale — Integrate & Govern
Add ERP/CRM integrations, agent-to-agent handoffs, and fine-grained RBAC across departments.
Phase 3
🏢
Enterprise — Full Coverage
All departments active with custom fine-tuned models. Predictive agents for forecasting at scale.
AI-BOX Agents

Pre-Built Agents for Every Department

Fully customizable agent templates ship with AI-BOX — ready to deploy from day one across your entire organization.

Finance
Accounts Payable
Financial Reporting
Expense Management
Budget Optimization
Fraud Detection
Human Resources
Recruitment Assistant
Employee Onboarding
Performance Mgmt
HR Policy Assistant
Payroll Support
Procurement
Vendor Management
Purchase Orders
Inventory Optimization
Supplier Negotiation
RFQ Processing
Sales & CX
Lead Qualification
Sales Proposal
Customer Segmentation
Sentiment Analysis
Feedback Analysis
Operations
Energy Management
Security Monitoring
Asset Tracking
Compliance Monitor
Meeting Assistant
How We Work

Engagement Models for Every Stage

From a two-week feasibility sprint to ongoing fractional AI leadership — ELMNTX meets you where you are and scales as you grow.

2 Weeks

Rapid AI Assessment

We audit your data, workflows, and team maturity to produce a practical AI roadmap with tooling TCO and prioritised use-cases.

→ Maturity heatmap · 12-week roadmap · TCO analysis
Monthly Retainer

Fractional AI/ML CTO

Ongoing strategic guidance without a full-time hire. Architecture reviews, vendor selection, and team upskilling as a managed service.

→ Architecture reviews · Upskilling · Vendor advisory
6–12 Weeks

Implementation Sprint

Build a production MVP — a deployed YOLO model, LLM/RAG pipeline, recommender, or conversational agent with a full runbook.

→ Working pipeline · Deployed model · Runbook
3 Days On-Site

MLOps Upskilling Workshop

Hands-on enablement for your team — CI/CD templates, guardrail policies, and a custom workshop tailored to your stack.

→ CI/CD templates · Guardrail policies · Playbook
Why ELMNTX

What Sets Us Apart

Eight principles that govern every engagement — from first advisory call to production deployment.

🏭

Production-First Delivery

No Jupyter notebooks as final output. Everything is tested, versioned, monitored, and documented for real-world operation.

📜

Governance as Code

Data lineage, column-level security, and model compliance baked into every pipeline — not bolted on after the fact.

🌐

Full-Spectrum AI

Not just LLMs. CV, RL, graph ML, time series, edge inference, XAI, and synthetic data — disciplines most consultancies sidestep.

🧲

Vector-Ready Data Engineering

Embedding pipelines and vector databases as first-class infrastructure citizens, designed from the ground up.

🧭

Vendor-Agnostic but Opinionated

We recommend based on workload and your objectives — not reseller agreements, platform incentives, or commissions.

☁️

Edge-to-Cloud MLOps

One unified framework for training on GPU clusters and inferring on a $10 MCU. One governance layer, end to end.

📊

Metric-Based Success

"Reduce time-to-insight from 5 days to 2 hours" or "deflect 40% of tier-1 tickets." We measure outcomes, not effort.

🏆

Owned AI IP

Tenzye, RoadBot, and AI-BOX give clients extensibility and security that pure advisory firms simply cannot offer.

12-Week Blueprint

Discovery to Production in 12 Weeks

Sample roadmap for Computer Vision — fully adaptable to LLM/RAG, recsys, time series, conversational AI, or AI-BOX deployment.

Wks 1–2

Discovery & AI Readiness

Use-case selection (e.g. manufacturing defect detection) + AI readiness report and full data audit with gap analysis.

Wks 3–4

Data Pipeline Build

Image ingestion → labeling (Label Studio / CVAT) → DVC versioning → Albumentations augmentation pipeline.

Wks 5–6

Model Development

YOLOv8 or Vision Transformer training + active learning loop to minimize labeling cost and maximize accuracy.

Wks 7–8

Edge Optimization

INT8 quantization + TensorRT deployment to target edge device (NVIDIA Jetson, Google Coral, or custom MCU).

Wks 9–10

MLOps & Monitoring

Drift detection (image histogram monitoring), automated retraining triggers, and canary deployment pipeline.

Wks 11–12

Integration & Handover

Inference API, observability dashboards, full production runbook, and team knowledge transfer sessions.

Ready to Move from AI Experimentation to Production Impact?

ELMNTX engineers, governs, and measures across every AI discipline — with our own secure products backing every engagement.