Describe the goal, current systems and constraints. We will review the scope and identify the next evaluation step.
Expected value, implementation cost, and the measurement method are agreed before development begins.
Milestones are set around data readiness, integrations, security review, and the production environment.
Current cost, cycle time, quality, capacity, or risk is established before improvement is measured.
Results are reported against approved source data, a defined system boundary, and an agreed measurement period.
ALLTIPLY connects AI models and agents to the systems your business runs on: ERP, CRM, data warehouses, ticketing, document stores and internal APIs. Integration is what turns a model that can answer into a system that can act.
Every connection is scoped to the permissions it needs, every read and write is logged, and actions with real consequences pass through an approval gate. The conversation-intelligence architecture report describes the demonstrated meeting records, prototype extraction and planned system joins. The operations-platform observations in the production-gap field report describe a built platform whose live data connections are planned.
These firsthand reports distinguish production use from proof environments and prototypes.
Explore our work and evidence status or read the research library directly.
Four phases from a system map to AI connected to production systems.
We map the systems involved, the data each AI step reads and writes, the actions it may take and the controls your security team requires.
We define interfaces, credential scopes, logging, approval gates and failure handling, and review them with your security and system owners.
We build the integrations, test them against staging systems with real cases, and verify that permissions, logs and approvals behave as designed.
Integrations go live with monitoring, alerting and runbooks, and we extend them as new models, agents and systems are added.
