SheraAIGlobalSheraAI Global / Services
Integrate language models into a useful application: provider connections, streaming interfaces, contextual retrieval and reviewable business workflows.
Define your project01 / PROJECT CONSIDERATIONS
A useful AI project starts with examples of the task and a clear definition of a good answer. We ask what information the system can use, which errors matter and when a person must take over. That makes a prototype measurable before a larger application is commissioned.
02 / PROJECT CONSIDERATIONS
The application needs authentication, input limits, provider credentials, streaming states and a way to handle unavailable services. SheraBot demonstrates provider selection, streamed conversations and local history. Those are concrete engineering foundations for a custom integration; they do not imply that SheraAI trains a proprietary foundation model.
03 / PROJECT CONSIDERATIONS
Where a knowledge workflow is appropriate, the scope can include retrieval from approved documents and references in the answer. Access rules should be enforced before information reaches the model. We consider what happens when the available material cannot answer a question and how corrections enter the source of truth.
04 / PROJECT CONSIDERATIONS
Model usage creates ongoing provider costs. Discovery reviews the data being sent, retention expectations, rate limits and evaluation cases. For actions with consequences, we define a review or confirmation step. Deployment and monitoring responsibilities are agreed rather than left inside an unowned API key.
05Relevant engineering
Explore the verified product work that informs this service. A new project receives its own scope and acceptance criteria.
Flutter interfaces, streaming provider integrations and local storage. Native provider keys use secure storage; a server proxy is the deployment path for shared provider credentials.
See the application to your project
REBUILT APPLICATION / DEVELOPMENT CAPTUREBefore the next step
Many business workflows can start with an existing model provider and a carefully designed application. We evaluate that route first. We do not claim foundation-model training as an established SheraAI capability.
A scoped retrieval workflow can use approved content if access and provider data handling are suitable. The first step is to identify the material, permissions and evaluation questions; confidential documents should not be sent in the initial brief.
No. Generative output can be incorrect. We design checks, source references where appropriate, evaluation examples and human review around the consequences of an error.
Connected reading
Custom website and internal assistants with approved knowledge, clear conversation boundaries and a useful path to a human.
Purpose-built software, internal tools and API integrations for workflows that do not fit an off-the-shelf product.
Connect repetitive work across forms, APIs and business systems with explicit rules, reliable retries and visible human ownership.