Workflow and system discovery
Trace one real request from its source to a completed result. Identify the records, decisions, permissions and people involved before selecting a model.
Workflow map; integration inventory; bounded initial scope.
AI integration.
Built around the work.
AI integration services connect models to the information, decisions and systems a business already uses. Daciel scopes the workflow, builds the integration and defines how people review the result.
When the work
needs to connect.
For teams moving beyond a standalone chatbot: a support desk that needs account context, a sales workflow that must write back to the CRM, or an operations team reconciling work across several systems.
What we do.
Connected implementation
Build the paths between approved systems and the AI workflow. Define input contracts, supported actions, validation and failure handling so an answer can become useful work.
System adapters; action contracts; approval and escalation paths.
Evaluation and release
Test representative tasks against explicit acceptance criteria. Review missing context, duplicate requests, timeouts and unsafe actions as well as the successful path.
Evaluation cases; release checks; reviewable execution records.
Operating model and handover
Document who owns each connection, how access is managed and what happens when a provider or business rule changes. Keep ongoing improvements tied to observed work.
Owner responsibilities; monitoring plan; maintenance and handover documentation.
How it moves.
Choose the first workflow
Start with a bounded business problem and the outcome the team needs. Agree which actions are read-only, which need approval and which should remain manual.
Build against real constraints
Use the existing systems, records and access rules to shape implementation. Models and providers follow the task; the business workflow should not depend on one model name.
Evaluate, release and operate
Review the execution and resulting records before widening the scope. Agree on ongoing support and on the evidence that will justify the next change.
Connected work.
A useful
first brief.
These details help us assess the work and propose a sensible scope.
- A representative task and an owner who can judge the result.
- The systems involved, available APIs and access constraints.
- Examples of successful work and cases that need human judgment.
- Data-handling, approval and operational requirements.
Before we start.
Do we need to replace our existing systems?
A discovery phase establishes which systems can remain and where connectors or changes are needed. An AI integration is not automatically a CRM, support-desk or finance-system replacement.
Can you work with different AI models?
Yes. Model selection and provider access are implementation choices. Daciel designs the workflow around explicit capabilities and evaluation criteria so a provider change can be assessed without redefining the business process.
How do you price an AI integration project?
The quote depends on the workflows, systems, data access, evaluation and operating requirements. We agree on scope and responsibilities before proposing delivery; third-party model and tool charges are identified separately where relevant.
Can we start through Daciel’s AI interface?
You can create an account to work directly with Daciel. If the requirement involves custom integrations, procurement or a tailored rollout, share the brief with the team so the delivery path fits the same business objective.