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Solutions / IA

Artificial intelligence agency for businesses

  1. $ need: Q&A assistant on internal documents
  2. ✓ need and user framing
  3. ✓ feasibility: data, security, costs
  4. → prototype on limited scope
  5. ● human validation for sensitive actions
Illustrative example

AI services

Artificial intelligence solutions designed for concrete needs

Artificial intelligence can help process information, assist users, automate certain tasks and enrich existing applications. Its relevance depends on the problem to solve, data quality, security constraints and expected reliability. Trivia Agency helps businesses identify use cases, design solutions and integrate them into existing tools.

Present my AI project
  1. 01

    AI model integration

    Integration of AI services into an existing application or process, according to the functional needs and project constraints.

  2. 02

    AI assistants and chatbots

    Creation of assistants capable of answering questions or guiding users based on defined sources and rules.

  3. 03

    AI-assisted automation

    Using AI to assist certain processing, classification, writing or analysis tasks, with risk-appropriate controls.

  4. 04

    Document analysis and processing

    Extraction, structuring or information retrieval in documents, where data quality and chosen models allow it.

  5. 05

    Business applications with AI

    Development of AI features integrated into web or mobile applications to meet a specific need.

  6. 06

    AI project consulting and framing

    Identification of use cases, required data and criteria to evaluate the value of a solution.

Value and limits

Using AI where it brings real value

Reduce certain manual tasks

AI can assist in processing repetitive tasks where the processes and data allow it.

Make information easier to access

Assistants can help find and summarise information from defined sources.

Enrich your existing tools

AI functions can be integrated into applications to complement existing journeys and services.

Explore new services

AI can allow new features to be tested, with gradual validation of their usefulness.

Method

From idea to deployment of an AI solution

  1. Step 01

    Needs framing

    We identify the business problem, the users involved and the expected outcome.

  2. Step 02

    Feasibility assessment

    We examine the data, existing systems, security constraints, costs and risks.

  3. Step 03

    Prototype and validation

    Where relevant, we test the use case on a limited scope and evaluate the results.

  4. Step 04

    Integration

    We integrate the solution into the relevant workflow or application, according to the agreed scope.

  5. Step 05

    Monitoring and improvement

    We can monitor results and adjust the solution according to feedback and evolving needs.

Data and security

AI integration designed with appropriate controls

Depending on the project, we examine the nature and quality of data, confidentiality, access rights, response reliability and usage costs. We promise neither total accuracy nor absolute security: guarantees are adapted to the solution, the provider and the context.

  • Data nature and quality

    A prerequisite assessed before any AI project.

  • Information confidentiality

    Data sent to AI services is examined according to its sensitivity.

  • Access rights and users

    Access management suited to the use case.

  • Response evaluation

    Possible errors are identified and measured.

  • Human oversight

    Human control for sensitive actions.

  • Usage costs

    Model limits and costs are taken into account.

  • Logging and monitoring

    Tracking set up where necessary.

Use cases

How can artificial intelligence help your business?

  • Q&A assistant from internal documents
  • Qualification or ranking of incoming requests
  • Information extraction from documents
  • Writing and summarisation assistance
  • Enhanced search in a knowledge base
  • Automation of certain process steps
  • AI features integrated into a business application
  • Customer assistant connected to authorised information

These examples are possibilities, not guaranteed outcomes. Feasibility must be validated for each context.

Proof

Project under assessment

AI solutions assessed for concrete needs

An assistant to find information in internal documents

Setting up an assistant capable of searching and summarising information from a defined set of documents, with human oversight on sensitive responses.

Discuss this type of project
What is the procedure to approve a client quote?
AI-generated response

According to the internal 'Sales' procedure, a quote is approved by the sales manager before sending.

Source: internal document (sales procedure) Human review required before any action
Illustrative example

Principles

An AI partner focused on business needs

Trivia Agency favours a pragmatic approach: start from a concrete need, assess feasibility and integrate AI where it can be useful, rather than adding it without a defined goal.

  1. 01

    Framing before model selection

    The business need is defined before the technical solution.

  2. 02

    Attention to confidentiality

    Data is handled with appropriate precautions.

  3. 03

    Evaluation of results and limits

    Every solution is measured, not just deployed.

  4. 04

    Integration with existing tools

    Where possible, without rebuilding everything.

  5. 05

    Cost consideration

    Including long-term maintenance costs.

FAQ

What services does an AI agency offer?

Depending on its expertise, an AI agency can support framing, prototyping, model integration, creating assistants and automating targeted tasks.

Can AI be integrated into an existing application?

Yes, if the application and the services involved have the necessary interfaces and if the security, cost and performance constraints are acceptable.

How much does an artificial intelligence project cost?

The budget depends on the use case, the level of integration, the required data, the chosen model and the validation and maintenance requirements.

Are AI responses always accurate?

No. AI systems can produce errors or incomplete responses. Results must be evaluated, high-risk uses limited and appropriate oversight planned.

Is my company's data protected?

That depends on the chosen architecture, the provider, the contractual terms and the data processed. Confidentiality conditions must be verified before any integration.

Can a process be fully automated using AI?

Some processes can be largely automated, but the level depends on the risk, data quality and reliability achieved. Human validation may still be required.

How do I know if an AI project is relevant?

Define the problem, the expected outcomes, the evaluation criteria, the costs and the risks. A limited prototype can help verify feasibility before wider deployment.

Let's assess the potential of AI for your business

Do you have a process to simplify, an assistant to create or an application to enrich with artificial intelligence? Tell us your need to explore the possibilities, constraints and next steps.