Introduction — why a dedicated channel-to-channel migration plan
Migrating legacy content to an AI reception avatar is not a simple copy of FAQs or IVR scripts. It means transforming often disparate sources into a knowledge base usable by semantic search and a RAG system, while ensuring service continuity for visitors and operations. This operational guide provides a pragmatic roadmap to move from existing content (FAQs, IVR scripts, web pages, business documents) to a conversational persona on a screen or kiosk, within a targeted project window of six to twelve weeks.
Step 0 - define scope and operational objectives
Before any migration work, clarify the functional scope of the avatar: which questions it must cover at launch, which channels remain active (IVR, human reception), and which regulatory or business constraints apply to responses. Define measurable objectives related to service continuity, coverage of frequent requests and acceptable switch-over times during the pilot. This clarification will help prioritize sources and balance accuracy, speed of delivery and transformation effort.
Step 1 - audit and map sources
Carry out a comprehensive inventory of available content: public and internal FAQs, IVR scripts (texts and trees), web pages, PDFs, internal guides, ticket databases and spreadsheets. For each source, capture useful metadata: business owner, estimated access frequency, language, last update date, format and level of granularity. The goal is not to document every word, but to produce a map that highlights where value and risk are concentrated.
The output of the audit is a simple dashboard per source that will feed prioritization: it identifies frequently consulted, expired, contradictory or missing content. This step prepares the selection of content that will populate the initial RAG base.
Step 2 - prioritize by business value and frequency
Prioritization should combine two axes: business value (perceived impact by operational teams) and frequency (requests actually raised by visitors). Focus first on high-repetition cases and those causing operational interruptions.
In practice, prioritize FAQs and IVR scripts that address practical, stable questions, then informational pages sensitive to compliance or timing. Highly volatile or heavily personalized content can be handled in a later phase. This approach reduces risk and speeds up delivery of a useful scope.
Step 3 - cleaning rules and canonicalization of content
Before ingestion, apply cleaning rules to avoid duplicates, contradictory answers and obsolete formulations. Typical operations include removing purely promotional elements, consolidating near-duplicate variants of the same response and validating critical information with business owners.
Canonicalization aims to maintain a single validated version of a piece of information. Define a priority rule between sources (for example: validated business documentation > public FAQ > IVR scripts) and keep a revision history. Ambiguous content should be flagged for review rather than published automatically.
Step 4 - transform content for an effective RAG
Adapting content for RAG means splitting it into fragments enriched with metadata to enable relevant semantic search. Each fragment should represent an autonomous idea or answer, with a title, business context, original language and topic tags.
Plan a metadata strategy that simplifies maintenance: origin, validation date, owner, confidence level, target audience. For structured documents, export to usable formats (PDF, DOCX, XLSX, TXT, CSV) is supported; structured knowledge can also be prepared in NDJSON according to the chosen workflow. Important: full translation of the knowledge base is not required by default. SANIA can communicate in more than 100 languages depending on configuration; prioritize linguistic coverage on the languages that matter for your visitors and test the quality of multilingual responses.
Step 5 - pilot strategy, coexistence with IVR and rollback
A progressive pilot allows you to validate quality without disrupting the existing service. During the pilot phase, run the avatar alongside the IVR: the avatar handles requests within the prioritized scope, and the IVR remains available for escalation or uncertainty. Clearly define the scenarios in which the avatar should prompt the user to contact a human team; it is recommended to plan messages that guide users to a human channel without implying an automatic transfer.
Prepare a rollback plan: stop conditions for the pilot, business acceptance criteria and the procedure to restore the previous configuration if needed. Pilot duration and acceptance thresholds depend on traffic and the objectives set by the organization.
Step 6 - multilingual testing, QA and acceptance
Tests must cover language variants and fallback cases. Build representative scenarios including simple questions, composite questions and ambiguous cases. Validate response consistency, the precision of RAG fragments and the relevance of metadata.
Involve business reviewers for validated content and set up an iterative correction process. Note that multilingual response quality also depends on the chosen LLM configuration; a multi-LLM orchestration may be considered depending on quality and cost priorities.
KPIs to monitor adoption and effectiveness
Choose indicators suited to your objectives and data collection tools. Examples of useful operational metrics: coverage of the prioritized scope (share of cases handled by the avatar), apparent resolution rate for interactions in the pilot scope, volume of escalations to humans and average resolution time after escalation. These metrics require a collection method defined by the organization; they are not provided automatically by default.
Complement with adoption KPIs: usage rate of equipped reception points, share of multilingual sessions handled and qualitative feedback collected via separate surveys. Plan regular reviews to adjust the knowledge base and system prompts.
Governance checklist and deliverable templates
Clear governance facilitates maintenance and compliance. Identify roles: business owner for each domain, content quality owner, technical reference for RAG ingestion and project manager for the pilot. Establish a content review calendar and a policy for validating updates.
Inventory of sources with metadata and prioritization
Fragmenting plan and metadata specification
Multilingual business test set and acceptance criteria
Pilot procedure, IVR coexistence message and rollback conditions
Version register and responsibility matrix for each content item
Deliverable templates to run the project in 6–12 weeks
For effective management, prepare simple actionable deliverables: prioritized inventory spreadsheet, RAG fragment template, QA checklist, multilingual test script and business acceptance report. These documents are used both to structure the work and to communicate with stakeholders.
An example operational sequencing for the recommended project window: scoping and audit week, weeks for cleaning and transforming prioritized content, weeks for testing and piloting in a controlled environment, then final review and ramp-up plan. Adjust cadence according to availability of business reviewers and site traffic.
Common mistakes and watch points
Frequent mistakes include: attempting to ingest all content at once without prioritization, neglecting canonicalization and leaving contradictory answers in place, or failing to involve business teams to validate critical information. Another pitfall is underestimating multilingual QA effort or assuming automatic translation is sufficient without business verification.
Also be sure to define clearly the situations where the avatar should invite the user to seek human help rather than presenting an uncertain answer. Finally, keep in mind that additional integrations (webhooks, external tools) will require specific development and are not provided by default.