[ GLOSSARY ]
The vocabulary we use on this site, defined once and cited from the same place. Levent-coined terms, reference terms used canonically across the industry, and the public catalogue of accelerator brands. Each entry has a stable anchor for citation.
The 12 Factor Agents framework is a set of engineering principles for building agentic systems that survive production. Inspired by Heroku's 12 Factor App, it covers context engineering, tool use, evaluation, observability, and statelessness as a discipline for agentic-AI delivery.
Agentic AI is the engineering discipline of building AI systems that take action, not just suggest it. They run multi-step work, call tools, and stand accountable for outcomes.
AgentOps is the production-operations discipline for AI agents. Observability, drift detection, token-cost governance, audit logging, and incident response for systems that decide and act, not just predict.
Where MLOps grew up around predictive models (versioning, retraining, drift), AgentOps grows up around agents that take action. The primitives transfer; the failure shapes do not.
Most agentic-native firms appearing since 2024 do not have the lineage. Levent carries fifteen years of MLOps DNA into AgentOps directly — same operating-model discipline, different decision surface.
A private RAG chatbot for compliance and policy archives. Citations on every answer. No data leaves the corporate firewall.
ATI, Agentic Transformative Intelligence, is the era where predictive models, autonomous agents, and an organisation's own secure data come together to make decisions, take actions, and stand accountable for outcomes across the enterprise.
ATI was named in a partnership conversation between Levent Analytics and Dataiku, and publicly introduced at the Dataiku Partner Event in November 2025.
It is the operational era between basic chatbots (AI that helps) and AGI (a horizon at least a decade away). ATI is what business leaders ship today.
A microservices reconciliation platform that matches invoices to purchase orders at scale, surfacing exceptions for human review.
BG/NBD-class probabilistic modelling that predicts high-value behaviour months ahead, integrated into Salesforce Marketing Cloud for automated segmentation.
Hierarchical SKU-and-store forecasting with automatic model selection. Procurement teams get a 12-month forward view that survives the long tail.
A document-centric workspace for purchase orders, invoices, and quotes, with secure server-to-server PDF generation and Firebase auth.
Foundation Phase is the initial six-month engagement Levent runs to take operational ownership of an AI platform. Knowledge transfer, automation, runbook delivery, and senior engineering embedded with the client team before the Managed Service phase begins.
The Foundation Phase exists because a clean Managed Service handover requires the operator to internalise the platform deeply — its data joins, its identity model, its failure shapes, its operating cadence. Six months is the smallest unit of time that delivers that on a complex enterprise estate.
Defensible attribution across 15+ channels, with an optimisation agent that turns the model into budget reallocation decisions.
A vendor-neutral runtime for composing multi-step AI workflows. Visual designer, pluggable integrations, real-time monitoring.
An AI-graded competition platform with Cloud Run-hosted evaluators on Gemini 3.1 Pro. Built for scale; deployed at an Indian institution.
IoT sensor telemetry plus historical maintenance data, fused into a rolling predictive maintenance schedule. Work orders fire before equipment fails.
MCP, Model Context Protocol, is the open standard for connecting agentic AI systems to external data and tools through a uniform server interface, allowing any agent runtime to call any tool without bespoke integration code.
MLOps is the production-operations discipline for machine-learning models. Versioning, retraining pipelines, feature stores, drift monitoring, and rollback — the operating layer that keeps predictive systems honest in production.
At Levent, MLOps and AgentOps are one continuous discipline. The model registry, the retraining pipeline, and the audit log are the same constructs whether the artefact is a forecasting model or an agent.
An agentic orchestration layer over an operational workflow. Decomposes job cards into tasks, runs the day's timesheet through a proprietary scheduling optimiser, auto-assigns work, and pushes status to customers.
Predictive AI is the machine-learning discipline of forecasting events, behaviours, and outcomes from historical data, deployed as a production system with MLOps rigour.
A six-category cost engine designed to mirror the factory's own cost-sheet methodology, with Gemini-powered PDF extraction and an approval-driven quotation workflow.
Production AI is AI that runs the work, not AI that runs in a notebook. A production AI system has audit trails, drift monitoring, rollback procedures, defined owners, and a retirement plan — not just a model that predicts well on a holdout set.
The distinction matters because the gap between a working demo and a production system is where most enterprise AI engagements stall. Levent's tagline — Beyond Pilots. Into Production. — names exactly this gap.
RAG, Retrieval Augmented Generation, is the architectural pattern where an LLM's generation step is grounded in retrieved passages from a private knowledge base, instead of relying solely on the model's training-time knowledge.
RAG is foundational to sovereign and regulated deployments because it keeps the answer-providing content inside the organisation's perimeter. Levent's Askive accelerator is a multi-agent RAG platform deployed entirely on sovereign infrastructure.
A hybrid recommendation engine combining collaborative filtering with content-based scoring, served at sub-50ms latency.
An autonomous AI recruiter on Google ADK. Processes resumes, scores candidate fit, and orchestrates interview pipelines without losing recruiter judgement.
Sovereign Agentic AI is agentic AI deployed inside a jurisdiction's data, regulatory, and infrastructure boundaries, built to meet UAE PDPL, KSA PDPL, and regional AI Council guidance from day one.
For GCC operators, sovereign architecture is the only way to deploy agentic systems on regulated data without violating residency or audit obligations. Public LLM API endpoints send data outside the jurisdiction; sovereign deployments keep inference, retrieval, logging, and key management inside the perimeter end-to-end.
A multi-tenant 3D sales experience that converts township CAD drawings into a live, interactive walkthrough. Sales teams configure plot availability; buyers explore at their own pace; leads land with the plot context attached.
[ READY FOR YOUR STORY? ]
