Smart Solutions, Real Impact
Your Vision, Our Craft
Connecting Your World
Mobiloitte offers enterprise AI & data solutions with Generative AI, LLMOps, MLOps, warehouse first analytics, and edge intelligence driving secure, rapid growth at business scale.
Convert taps to revenue insights with real-time streams, cohorts.
Shift sessions to strategy with dbt models, hybrid tracking, funnels, cohorts, and MMM..
Chain-speed risk, alpha & compliance via multi-chain data, clustering, MEV tracking & ML alerts.
Responsible GenAI with RAG to cut hallucinations, fine-tuning, LoRA, and LLMOps guardrails & CI/CD.
LLM agents with RAG, workflows, multi-channel adapters, & safety guardrails.
Data-driven decisions with dbt metrics, real-time Kafka/Flink analytics, causal inference & automation.
Frictionless data platforms: lakehouse, streaming, feature stores & RAG-ready.
Edge intelligence: quantized models, federated learning, privacy analytics, anomaly detection.
Fast, safe AI everywhere: model-agnostic gateway, RAG/vector DBs, tool calling with RBAC & audit.
Turn taps into revenue insights with real-time streams, cohorts, funnels & MLOps churn/LTV.
Shift sessions to strategy with dbt models, hybrid tracking & full-stack funnels, cohorts, MMM.
Bots beyond chat: LLM agents with RAG, workflows, multi-channel adapters & strong safety guardrails.
Frictionless data platforms: lakehouse, streaming, quality, lineage, SLOs, feature stores & RAG-ready.
Edge intelligence: quantized models, federated learning, privacy analytics, maintenance & anomaly detection.
Mobiloitte’s AI & Data Solutions team blends strict engineering with thoughtful design. Platforms are secure, observable, and governed and paired with a culture of experimentation so teams turn insights into lasting advantages.
Built for production with CI/CD, LLMOps/MLOps, and SLAs.
Fast RO MVPs in weeks, scaling without re-platforming.
Enterprise-ready from day one: SOC 2, GDPR, HIPAA, PCI.
Built to adapt: switch clouds, models, or tools without lock-in.
Engagements move from idea to governed MVP to enterprise scale in three iterative sprints, each measured for ROI and security.
High-value use cases, data readiness, compliance needs, and KPIs are mapped. Output: an agreed architecture and ROI blueprint.
Pipelines, models, RAG/LLM agents, dashboards, and guardrails are shipped with CI/CD and LLMOps and MLOps services. Validation uses real traffic and gold-standard evals.
Quality, cost, and risk are monitored; models are retrained and improved. Rollouts expand to new teams and regions under SLAs with continuous-improvement loops.
Build manageable, high-impact AI with well-designed data and model building blocks.
Mobiloitte provides model-agnostic architectures with governance, LLMOps and MLOps services, and FinOps built in. This approach allows cloud or model changes without re-platforming while maintaining cost, security, and auditability.
Most clients reach a pilot in 4–6 weeks RAG/fine-tuned models, dashboards, or edge inference under SLAs. Enterprise rollout across teams and regions generally follows in 8–12+ weeks with compliance hardening.
Yes. Self-hosted LLMs, vector DBs, and data pipelines can run in a private cloud or on bare metal. Guardrails, eval suites, and cost monitoring remain in place while data stays inside the perimeter.
Dynamic model routing, caching, quantisation, and prompt compression reduce spending, with live cost dashboards. Teams see cost per successful task and can enforce budgets or automatic fallbacks.
Architectures align with SOC 2, GDPR, HIPAA, PCI, and ISO/IEC 42001. RBAC/ABAC, PII masking, prompt isolation, audit logs, and red-team testing support board- and regulator-grade assurance.
Design favours human-in-the-loop augmentation. Bots handle repeatable tasks; people focus on strategy and edge cases. Autonomy increases safely using eval scores and policy guardrails.
Adapter layers and secure APIs connect modern pipelines to mainframes, on-prem databases, or proprietary ERPs. Where direct links are not possible, event/file bridges move data with the same governance and lineage
A dedicated 24/7 support pod uses incident playbooks, runbooks, and quarterly health checks. SLAs cover availability, latency, data freshness, and response times with clear escalation paths.
KPIs such as deflection %, churn reduction, and DSO are set during discovery. Dashboards compare uplift to controls and track cost per win, so finance and leadership see payback in real time.
Fine-grained RBAC/ABAC, masking, and tenancy boundaries are enforced in warehouses, lakehouses, and vector stores. Policies are code-enforced and auto-audited and vital for GDPR or HIPAA across regions.
Yes. Platforms are modular: begin with a high-ROI pilot, then add domains, models, or geographies using the same governance, CI/CD, and cost-monitoring scaffolding no forklift upgrades.
Engineers use dbt, Airflow/Prefect, vector DBs, and LLMOps and MLOps services toolchains. Documentation, code walkthroughs, and enablement workshops are provided, with co-managed options until teams are fully ready.