AI features for existing applications
Add scoped capabilities such as summarization, semantic search, categorization, or writing assistance to an existing product or internal application.
Software / AI applications
AI application development for practical tasks.
Design and build practical AI features for your products and business workflows. Evolext can help you explore a use case, create a prototype, and integrate selected AI capabilities into a web or mobile application.
For small and medium-sized businesses, including those without an in-house technology team, exploring an AI feature, a knowledge assistant, or a defined workflow.
Discuss your project ↗01Define the task
02Review data
03Prototype and test
04Integrate and hand over
01 / When this service helps
When this service helps
Recognize your project
- You have a specific task where summarization, search, classification, or drafting could help.
- You want to explore a potential AI feature before committing to a full implementation.
- You need to review an existing AI integration and identify improvements.
Choosing the right service
- A conventional search or rules-based workflow may be sufficient for some tasks.
- The appropriate approach depends on available data, desired review, costs, and the consequences of errors.
What Evolext can build
These are possible project types, not a portfolio or a fixed package. Features and deliverables are agreed for your project.
AI knowledge assistants
Help people find answers in selected documents, support articles, or product information, with source references where supported and appropriate.
AI workflow automation
Support a defined process such as extracting document information, sorting inquiries, or drafting responses. Agree where a person reviews outputs before further action.
02 / Capabilities that support your goal
Capabilities that support your goal
AI features and integration
Define the user task, connect an agreed AI provider to the application, and review the resulting experience with representative examples.
Knowledge assistants
Select source material and access boundaries, then develop an assistant that retrieves relevant information and can show its sources where appropriate.
Workflow automation
Integrate AI into a bounded process and define review steps before messages are sent or important records are changed.
Prototypes and feasibility assessments
Explore a specific use case through a scoped assessment or prototype, documenting observations, provider costs, limitations, and possible next steps.
Integration review and improvement
Review an existing AI feature for selected issues such as unreliable outputs, sensitive-data handling, and usability; agree any further testing or improvements separately.
03 / How the work proceeds
How the work proceeds
- 01
Define the use case
Agree the task, intended users, current process, success criteria, and consequences of errors.
- 02
Review data and options
Discuss available sources, access, provider choices, data handling, costs, and whether AI is appropriate.
- 03
Prototype or build
Implement the agreed scope and review representative examples with the people responsible for the workflow.
- 04
Test and hand over
Document test observations, limitations, provider dependencies, human review steps, and operational responsibilities.
04 / What you can take forward
What you can take forward
Outputs defined with your scope
- A scoped assessment, prototype, review, or application integration as agreed.
- Notes on representative tests, observed limitations, provider dependencies, and handover responsibilities.
Factors to plan for
- AI outputs can be inaccurate or incomplete and may require human review.
- Provider charges, data handling, access controls, ongoing maintenance, and production deployment depend on the agreed scope.
05 / Illustrative engagement
Help teams find answers in their own knowledge.
Fictional example for explaining scope. It is not a client project or promised result.
AIIllustrative concept · not a client project
Example sourceAccount recovery guide
A team member checks the source and reviews the answer before acting.
A product team wants staff to find answers in selected support documents without searching through each one manually.
- Example inputs
- Approved support documents, intended users, access rules, and a set of representative questions.
- Example activities
- Define the scope, build a prototype that retrieves relevant passages, and review sample answers and source references with the team.
- Example outputs
- A prototype for the agreed use case, plus test observations, known limitations, provider dependencies, and decisions for the next stage.
06 / Helpful details to get started
Helpful details to get started
- The task, intended users, and the workflow you want to improve.
- Existing application or source information, access constraints, and provider preferences if known.
- Examples of useful results and the level of human review needed.
07 / Common questions
Common questions
Do we need AI for our task?
Not always. A scoped assessment can compare AI with simpler search or rules-based approaches against your requirements.
Can the assistant use our documents?
Selected sources can be considered after reviewing permissions, data handling, access controls, and the chosen provider.
Will the results always be correct?
No. Outputs can be wrong or incomplete. Testing and human review should match the use case and the consequences of mistakes.
Are provider fees and maintenance included?
Provider charges, ongoing maintenance, and deployment responsibilities are agreed for each project.
09 / Discuss your project
Start with the task you want to improve.
Share the goal, intended users, and any existing application or information sources. A high-level outline is enough; please do not send credentials or sensitive records through the inquiry form.
Discuss your project ↗