ELMNTX moves enterprises from AI experimentation to production-grade impact — with vendor-agnostic advisory, hands-on implementation, and MLOps governance across every AI discipline.
From generative AI to edge inference, we cover every layer of the modern AI stack with production-grade delivery and measurable outcomes.
RAG architectures, fine-tuning (Llama 3, Mistral, GPT-4, Claude), multi-modal GenAI, safety guardrails, PII redaction, and hallucination detection.
Predictive & prescriptive ML — demand forecasting, churn, uplift modeling. Responsible AI with SHAP/LIME explainability and legacy SAS/R modernization.
Defect detection, medical imaging, retail shelf analytics, CCTV anomaly detection. YOLOv8, SAM, ViT, DeepSORT — from labeling to edge inference.
Information extraction, multilingual NLP, document understanding (LayoutLM), sentiment & emotion detection, legal and medical text analytics.
LLM selection, orchestration & routing. CI/CD for ML, canary deployments, prompt tracing, token cost tracking, drift detection with LangSmith / Arize.
Dynamic pricing, inventory optimization, multi-agent fleet coordination. Sim2Real advisory: train in Unity / NVIDIA Isaac, deploy to real environments.
Knowledge graphs, fraud ring detection via GNNs, supply chain risk modeling, anti-money laundering. Graph RAG for enhanced retrieval pipelines.
Demand, energy, and IoT telemetry forecasting with Prophet, DeepAR, TFT. Real-time anomaly detection with autoencoders and causal ML root-cause analysis.
Two-tower neural recsys, session-based GNNs, contextual bandits, real-time vector search with Milvus / Qdrant, and online A/B interleaving evaluation.
Quantization (INT8), pruning, distillation for MCUs and Raspberry Pi. Federated learning across edge devices — healthcare, mobile, and IoT without data centralization.
SHAP, LIME, counterfactuals, adversarial testing (Foolbox / CleverHans), Constitutional AI alignment layers, and interpretable model alternatives like GAMs.
CTGAN/TVAE for tabular privacy, StyleGAN & diffusion for rare defect image generation, LLM-augmented text augmentation and time-series GANs for sensor data.
"Garbage in, GenAI garbage out."
We ensure your data is reliable, fresh, and governed before a single model is trained. Every AI engagement starts with a data readiness audit.
Two production-ready AI platforms you deploy in your own environment. Zero data leakage. Rapid time to value.
Automates tender sourcing, document parsing, compliance checks, and bid evaluation using LLMs + graph ML. Explainable, bias-free, and fully tenant-isolated.
Orchestrates RPA + LLM + computer vision to automate document-heavy, cross-system processes: invoice-to-pay, contract-to-compliance, road inspection and beyond.
A turnkey enterprise AI platform that transforms organizations with next-generation AI agents — without exposing a single byte to public models.
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
Deploy 2–3 agents (e.g. Expense Management + Meeting Assistant) for one department. Measure ROI and adoption in 4 weeks.
Add ERP/CRM integrations, enable agent-to-agent handoffs, and implement fine-grained RBAC across departments.
All departments active with custom fine-tuned models. Predictive agents for forecasting and anomaly detection at scale.
Fully customizable agent templates ship with AI-BOX — ready to deploy from day one across your entire organization.
From a two-week feasibility sprint to ongoing fractional AI leadership — ELMNTX meets you where you are and scales as you grow.
We audit your data, workflows, and team maturity to produce a practical AI roadmap with tooling TCO and prioritised use-cases.
Ongoing strategic guidance without a full-time hire. Architecture reviews, vendor selection, and team upskilling as a managed service.
Build a production MVP — a deployed YOLO model, LLM/RAG pipeline, recommender, or conversational agent with a full runbook.
Hands-on enablement for your team — CI/CD templates, guardrail policies, and a custom workshop tailored to your stack.
Eight principles that govern every engagement — from first advisory call to production deployment.
No Jupyter notebooks as final output. Everything is tested, versioned, monitored, and documented for real-world operation.
Data lineage, column-level security, and model compliance baked into every pipeline — not bolted on after the fact.
Not just LLMs. CV, RL, graph ML, time series, edge inference, XAI, and synthetic data — disciplines most consultancies sidestep.
Embedding pipelines and vector databases as first-class infrastructure citizens, designed from the ground up — never an afterthought.
We recommend based on workload and your objectives — not reseller agreements, platform incentives, or commissions.
One unified framework for training on GPU clusters and inferring on a $10 MCU. One governance layer, end to end.
"Reduce time-to-insight from 5 days to 2 hours" or "deflect 40% of tier-1 tickets." We measure outcomes, not effort.
Tenzye, Roadbot.io, and AI-BOX give clients extensibility and security that pure advisory firms simply cannot offer.
Sample roadmap for Computer Vision — fully adaptable to LLM/RAG, recsys, time series, conversational AI, or AI-BOX deployment.
Use-case selection (e.g. manufacturing defect detection) + AI readiness report and full data audit with gap analysis.
Image ingestion → labeling (Label Studio / CVAT) → DVC versioning → Albumentations augmentation pipeline.
YOLOv8 or Vision Transformer training + active learning loop to minimize labeling cost and maximize accuracy.
INT8 quantization + TensorRT deployment to target edge device (NVIDIA Jetson, Google Coral, or custom MCU).
Drift detection (image histogram monitoring), automated retraining triggers, and canary deployment pipeline.
Inference API, observability dashboards, full production runbook, and team knowledge transfer sessions.