Enterprise solutions for AI and systems
We help enterprise teams put AI into working processes and plan the technical architecture around them, from legacy stacks to cloud infrastructure and security.
Capabilities for practical deployment
AI implementation partner
We integrate machine learning models into live workflows, so predictions reach the people and systems that act on them.
IT technical consulting
We review cloud infrastructure, security postures, and legacy stacks to shape architecture decisions before work begins.
System integration roadmaps
We build resilient integrations that support real business operations without adding unnecessary complexity.
From assessment to operational handoff
Each engagement moves through architecture assessment, a proof of concept, deployment, and a clear handoff to the teams who will run the system.
01 / Architecture assessment
We map the current stack and the target state before choosing an approach.
02 / Proof of concept
We test the integration on a limited scope to confirm the approach holds.
03 / Deployment
We roll the solution into live operations in controlled, measured steps.
04 / Operational handoff
We transfer documentation and knowledge so your teams can run the system confidently.
Enterprise AI solutions built around your workflows
Connect approved knowledge and business systems so teams can find answers, prepare actions and review operational data. Zerosandones delivers the consulting, integration and adoption work around CAIA Platform.
Business assistants with CAIA Studios
Support care, sales, finance, procurement and operations with answers grounded in approved documents and connected systems. Scope each assistant to its team and require approval for write actions.
Team and incident assistants
Bring approved knowledge and system lookups into supported meetings and incident bridges. Prepare source-backed answers and incident notes while the incident commander retains decisions.
Engineering support with CAIA Coder
Help engineers investigate incidents, prepare code changes and tests, and work with approved repositories and environments. Engineers retain review, merge and production change approval.
Conversational analytics with AILytics
Ask questions against approved data sources, explore dashboards and prepare recurring reports. Validate generated queries and reconcile the results with agreed business definitions.
Private models with ML Fabric
Plan model selection, routing, evaluation and deployment around data sensitivity, latency and cost. Private cloud, on-premises and hybrid options depend on the agreed architecture and platform configuration.
A pilot with evidence at the end
Select one team and a bounded workflow. Establish current performance, connect a limited set of systems, test on representative cases and compare outcomes. Agree the decision to expand using answer accuracy, task completion, handling time and total operating cost.
Example workflows
Telecom and IT operations — incident context and runbook retrieval. Finance — invoice status and recurring management reports. Sales — account briefs and CRM updates with approval. Engineering — incident investigation and reviewed test or code suggestions.
Designed around your controls
Define source access, role permissions, data retention and approval boundaries before deployment. Confirm connector support, hosting, model costs and security requirements during discovery.