AI, cloud, security, architecture, engineering and business experts work as one team, from strategy to systems running in your organization.
Most AI projects stall on the same issues, and the model is rarely one of them. Data, security and ownership are. That is why every discipline is involved from the first day.
No plan for infrastructure, high concurrent, ownership or running cost.
No clear owners, data structures are not tested, and permissions differ from system to system.
Data questions come up at the end instead of being settled in the design.
VIEWINGAI Agent
From planning and building to migrating, rolling out and running systems after launch. Every service is measured, your data stays in your control, and what we build is yours to run.
Keep systems running
Build AI systems and software
Move systems and data to the cloud
Change how the organization works with AI
Modernize existing applications
Roll out and connect systems
Corporate AI as SaaS or dedicated
Find out how ready you are first
Retrieve permitted evidence
SECURITY + GOVERNANCE: SSO / RBAC, PII controls, Encryption, Audit, Retention, Injection defenses
OPERATIONS + QUALITY: Traces, Retrieval + answer evals, Latency / cost budgets, CI/CD + rollback, Alerts + recovery
OWNERSHIP: Data owner, Platform, Security, AI engineering, Product
SUCCESS METRICS: Answer quality, Task success, p95 latency, Cost per task, Adoption
Reference architecture for a knowledge and agent system. Each layer has a team that owns it.
Executives, finance, IT, security, business teams and the public sector ask different questions. Pick yours to see what you get, and the evidence you need to decide.
Map your data, systems and processes, pick the use case with the best return, and agree on the metrics.
DecisionIs this the right problem to start with, and how will it be measured?Build a small version on your real data, put it in front of real users, and measure it against the metrics.
DecisionDid the results meet the agreed bar?Run the security review, add monitoring, and deploy on the infrastructure you choose.
DecisionIs it ready to go live and hand over?Extend to more teams, train your people, and hand over so your team can run it.
DecisionWhat is worth scaling next?This is the log a single question to the AI leaves behind. Each line is evidence for a commitment below.
whereChoose the cloud region or run in your own data center, with model training on your data turned off.
whoThrough SSO, the AI shows people only what their existing permissions allow; agents get their own.
traceEvery question, answer, cited document and agent action is logged.
req 7f3a-0291 · 14:32:07 +07logged Illustrative data showing what is recorded for each request.
Answer 13 questions across 6 areas in about 5 minutes and get a result like this one straight away.
scoreStrategy, data, cloud, security, engineering and AI experience are scored separately, so you see what is ready and what is not.
gapsYour weakest areas, with advice on where to start.
scopeYour readiness level and the phases to start with, ready to discuss with our team.
readiness 52 / 100result Example figures. Your result depends on your answers.
No preparation needed. Tell us briefly what you want to solve, and the right specialists will get back to you.