CEDURA combines data science, AI engineering, and product thinking to discover high‑impact use
cases,
prototype quickly, and launch production‑ready AI experiences your teams and
customers can trust.
We help teams turn AI ideas into reliable shipped features, with clear visibility into performance, costs, and risk at every step.
Our Support Group
We turn ambiguous AI ideas into production features your users trust—combining
strategy,
design, engineering, and rigorous evaluation.
We focus on the metrics that matter—accuracy, latency, safety, and cost—so every iteration delivers measurable business impact, not just experimental models or demos.
From day one, we run offline and online evaluations, canary deployments, and system tracing—giving full visibility into model behavior, failures, and performance improvements over time.
Identity controls, PII handling, encryption, RBAC, and audit logging are embedded by default—ensuring AI systems meet enterprise security and compliance standards from day one.
We design prompts, workflows, and interfaces that feel intuitive and reliable—reducing friction for users while ensuring AI systems remain transparent and controllable.
Turn repetitive tasks into autonomous flows—agents plan, execute, and report with guardrails, audit trails, and clear human handoff.
Measure accuracy, latency, safety, and cost from day one. Built-in evals and dashboards keep systems reliable and spend predictable.
Activate internal docs, tickets, and wikis with retrieval-augmented generation, including freshness, citations, and traceability.
Interfaces, prompts, and error states designed for trust and adoption—so intelligent systems feel intuitive and dependable.
PII handling, SSO/SAML, RBAC, secrets management, and compliance workflows ensure enterprise-grade security by default.
Connect seamlessly to CRMs, ERPs, data warehouses, and APIs to operationalize AI insights across your stack.
Retail markets are intensely competitive—discounts, fast delivery, and good UX are table stakes. In this study we surface hidden opportunities in distributed store networks to offer personalised services and grow lifetime value.
There is no one‑size‑fits‑all campaign. This study explores how AI helps marketers move beyond trial‑and‑error, using behavioural signals to select channels, creatives, and timing that maximise reach and engagement.
The complexity of modern financial products attracts fraud, identity theft, and abuse. We show how AI‑based risk scoring and anomaly detection mitigate threats while keeping genuine transactions smooth and trusted.
Many things can happen over a cup of coffee. We use analytics and visualisation to support decisions from menu design and stock management to demand‑based staffing and offers—creating memorable experiences at scale.
Forecasting, routing, and quality‑control models help manufacturers anticipate demand, reduce waste, and keep production resilient in the face of upstream and downstream disruption.
From triage to risk stratification, AI can support clinicians without replacing judgement. This study shows how to embed models with strong evaluation, safety, and workflow alignment.
Usage, support, and revenue signals feed scoring models that power in‑product assistants, success playbooks, and pricing experiments—so every release learns from the last.
