Conversational
Experiences
Give users a natural-language way to access information or complete defined tasks when conversation fits the product journey.
Help users find answers, work with information, and complete tasks through thoughtfully designed AI features. WDI develops AI web applications with clear user controls, relevant integrations, and functionality grounded in your business needs.
The starting point is a specific interaction or workflow that benefits from AI.
Give users a natural-language way to access information or complete defined tasks when conversation fits the product journey.
Use suitable information and product context to surface options, content or actions against a defined relevance objective.
Help users retrieve, interpret or summarise information from agreed sources, with permissions and expected response behaviour considered during planning.
Support users through tasks that involve interpreting information, preparing inputs or organising material for the next stage of work.
Introduce extraction, classification or summarisation into applications handling suitable documents and business inputs.
Use appropriate historical data for forecasting, classification or other defined predictive functions where evaluation is feasible.
Define the user task, the role AI should play and the criteria for assessing usefulness.
WDI reviews the product context before translating an AI opportunity into application scope.
Best suited for: Teams defining an AI feature before implementation.
Design web interactions that let users work with information or functionality through natural language.
Planning establishes sources, permissions, response expectations, evaluation and fallback behaviour.
Best suited for: Products where conversational interaction supports an established user task.
Plan recommendations around a clear relevance problem and suitable product information or user signals.
The scope should define how recommendations are assessed and how the product behaves when inputs are limited.
Best suited for: Web products with a specific use case for tailored options or content.
Integrate AI where users benefit from assistance with interpreting, organising or preparing information.
Human review and exception handling depend on how the output will be used in the next step of the workflow.
Best suited for: Information-heavy customer or operational applications.
Review the existing frontend, backend, APIs and workflows before defining integration.
Some products can accommodate targeted additions; others may need supporting application changes.
Best suited for: Established web products adding focused AI functionality.
Develop the product experience around the AI capability, including interfaces, application logic, backends and APIs.
The AI interaction should operate within the same permissions, workflows and ownership model as the wider application.
Best suited for: Teams requiring both web engineering and AI implementation.
The capability should follow the task.
A conversational way to complete a defined task.
Surface options against a defined relevance goal.
Retrieve answers from sources the product may use.
Help users through an information-heavy task.
Extract or summarise suitable document inputs.
Forecast where the outcome can be evaluated.
Add AI within the current architecture and APIs.
Keep a person in the workflow when needed.
The capability should follow the task, and planning should establish what users can rely on.
Product planning needs to establish what users can rely on, what information the feature may use and when the workflow should involve a person.
A useful release plan shows that the product, information and operations are ready.
Evaluation should match the task. The application also needs an agreed path when output is uncertain, incomplete or unavailable, with human review where relying on that output requires a person. That path belongs in the release plan, next to the criteria used to accept the feature.
Related routes: Web Development, Web Application Development, SaaS Application Development, Artificial Intelligence Development Services and AI Mobile App Development.
AI can affect data flows, application behaviour and operational responsibilities beyond the visible interaction.
The task or experience AI should support
Why AI is useful in that interaction
Available sources, suitability and ownership
Where AI belongs in the product journey
Frontend, backend, APIs and dependencies
Who can access information and how it may be used
Criteria for assessing output and usefulness
Review, intervention or escalation requirements
What happens when output is incomplete or unavailable
Who monitors and manages the feature
This assessment establishes suitability before the team selects an implementation.
Clarify users, the application workflow and the intended AI role.
Clarify users, the application workflow and the intended AI role.
Review sources, architecture, APIs, permissions and constraints.
Review sources, architecture, APIs, permissions and constraints.
Identify the assumptions and evaluation criteria needed to assess suitability.
Identify the assumptions and evaluation criteria needed to assess suitability.
Map interactions, interface states, human review and fallback paths.
Map interactions, interface states, human review and fallback paths.
Engineer the web application and AI capability with the required systems.
Engineer the web application and AI capability with the required systems.
Test application workflows and AI behaviour against agreed criteria.
Test application workflows and AI behaviour against agreed criteria.
Where continued support is included, use product and operational evidence to guide changes.
Where continued support is included, use product and operational evidence to guide changes.
A fraction of what we have shipped.
The application, its source information and user expectations can change after the first AI-enabled release.
AI ownership therefore needs to include a basis for reviewing the feature over time.
Connects the AI capability to one defined user task
Places the AI feature inside a coherent product journey
Coordinates the interface, AI services, backends and APIs
Defines how the team will assess usefulness over time
Establishes where people remain involved
Assigns who monitors and reviews the feature after release
Where ongoing support is included, subsequent changes should be informed by the agreed evaluation criteria and product evidence.
Look for a team that can explain both the AI task and the application around it.
The partner should connect information sources, permissions, application workflows and ownership, and explain how output is evaluated when a result is unavailable or needs a person to review it before the user continues.
Discuss Your AI Web Application ProjectIntegration may be practical when the application’s architecture, APIs, information sources and workflows provide a suitable foundation. Discovery identifies integration points and any supporting changes required before implementation.
The inputs depend on the task. Recommendations, document processing, conversational interaction and predictive features can require different information. Planning should establish source availability, ownership, permissions and how output will be evaluated.
Evaluation should reflect its intended use. Criteria may include relevance, completeness, consistency, recommendation usefulness and human-review findings. Application behaviour and fallback paths also need to be tested.
The level of review depends on the task, how the output is used and the consequences of an incorrect or incomplete response. Review, approval and escalation should be defined for the particular workflow.
General Web Application Development focuses on browser-based workflows and software logic. This service is more specific when AI is meaningful to the product and introduces additional requirements around information, evaluation, human oversight and monitoring.
Artificial Intelligence Development Services addresses broader AI opportunities and implementation choices. This page focuses on AI within a web application experience, including its interfaces, workflows and supporting application engineering.
Share the web product you are building or improving, its users, the AI feature under consideration and the application, information or integration requirements already known.
WDI will review the intended experience, current architecture and dependencies to help define the next step. This may involve discovery, opportunity assessment, technical validation, experience design or implementation planning.
