Design & Implementation
We turn strategy into shipped systems – designing the edge‑to‑cloud architecture, defining your AI and Edge stacks, selecting the right vendors, and building the minimal, production‑ready path that proves value and scales. Our focus is on measurable outcomes: faster decisions, lower cost‑to‑serve, and resilient operations across sites, devices, and teams.
We blueprint the data flows, security guardrails, and operating model, then implement with disciplined delivery: reference architectures, IaC, Orchestration layer and MLOps that fit your constraints. Each build is time‑boxed, integration‑light, and instrumented end‑to‑end so you can see what’s working, what it costs, and what to scale next.
From strategy to enterprise value, that is delivered fast, safe and is scalable.
How It Works
- Clarify scope and KPIs; convert use cases into technical epics with acceptance criteria.
- Design edge–cloud split, data contracts, and security patterns with rollback paths.
- Select vendors and open‑source components with lock‑in minimization and exit ramps.
- Implement via IaC, containerization, orchestration, and CI/CD for apps and models.
- Instrument telemetry, cost, and reliability from day one for objective readouts.
What You Get
- Reference architecture and deployment topology tailored to your sites and workloads.
- Production‑ready “thin slice” that proves value with minimal integration overhead.
- Orchestrated edge fleet, OTA update process, and model packaging/versioning.
- Policy guardrails: identity, secrets, data retention, and model‑risk controls.
- Decision memo with rollout options, dependencies, cost bands, and owners.
Success Metrics
- Time‑to‑first‑value measured in weeks, not quarters.
- KPI lift: latency reduction, throughput gains, and workflow time saved.
- Reliability: SLO adherence, rollback speed, and incident rate trending down.
- Cost‑to‑serve improvements: backhaul, compute, storage, and support delta.
- Delivery velocity: changes per week and lead time from commit to production.
Enablement & Support
We enable your teams to own the solution, through training, playbooks, and on‑call support that fit your operating rhythm. Adoption is deliberate: we equip business, IT, and ops with the skills, runbooks, and metrics to run, improve, and expand the deployed stack without vendor dependency.
Our support model blends proactive governance with practical help: rollout rings, SRE‑style observability, model monitoring, and incident response tuned to edge realities and regulatory needs. You get confidence at scale, with clear SLAs, transparent costs, and a roadmap to reduce external reliance over time.
From go‑live to enduring value, that is operated fast, safe and is scalable.
How It Works
- Role‑based training for product, ops, IT, and data/ML teams with hands‑on labs.
- Playbooks and runbooks: deployment, rollback, incident triage, and change management.
- Observability setup: logs, metrics, traces, model drift, and user adoption telemetry.
- Governance cadence: KPI/SLO reviews, risk assessments, and release planning.
- Support tiers with clear SLAs, escalation paths, and executive communication.
What You Get
- Practical enablement assets: admin guides, SOPs, architecture docs, and FAQs.
- A knowledge base and office‑hours program to speed internal autonomy.
- Cost and performance dashboards for finance, product, and operations leadership.
- Security and compliance artifacts to satisfy audits and customer diligence.
- A roadmap to transition from co‑managed to self‑managed operations.
Success Metrics
- Adoption and utilization thresholds by role, function, and site.
- Mean time to detect/resolve incidents trending down; rollback time under target.
- Model and app health: drift alerts closed within SLA; retrain cadence achieved.
- Release reliability: % deployments via automated pipeline, change failure rate.
- Self‑sufficiency: reduced external tickets and increased internal first‑call resolution.