Build what is missing.
Connect what already works.
AI applications, speech-to-text systems and supporting infrastructure, engineered for environments where data, access and deployment need to remain under your control.
Wentland designs and integrates the complete system, from compute and models to the applications and workflows that use them.
START WITH THE REQUIREMENT
Decide what the system must do.
And where it is allowed to do it.
An AI use case becomes an engineering requirement when it has to work with real data, real users and existing controls.
We establish the task, the information involved, the required response times and the applications the system must connect to. Those requirements guide model selection, compute and storage, access controls and deployment.
On-premise or private infrastructure may be appropriate where information handling, connectivity or ownership needs rule out a public-cloud-only approach. The choice follows the requirement, not a preference for one deployment model.
AI SYSTEMS ENGINEERING
What we engineer and integrate.
Applications, models, devices and infrastructure are considered as parts of the same system with a defined purpose for each.
01 AI-Enabled Applications
Develop applications that use AI for classification, extraction, summarisation and information handling.
We connect the model to the interface, permissions and workflow in which the result is used, including review steps where required.
02 Speech-to-Text Systems
Deploy private speech-to-text systems with the audio input, processing environment, storage and application integration designed together.
Access to recordings and transcripts, retention requirements and the review of generated text form part of the system design.
03 Embedded AI Devices
Integrate AI-enabled devices into the wider environment, including their connectivity, data exchange, access and supporting services.
We establish which processing belongs on the device and which belongs in the private backend, according to the requirement.
04 AI Backend & Infrastructure
Size compute, memory and storage for the selected models and expected usage.
We implement the backend services and interfaces required to run inference and make it available to authorised applications within the chosen environment.
05 AI Integration
Connect AI outputs to existing applications, APIs and business workflows.
We define what information the system receives, what it returns, who can access it and where review or approval is needed before the result is used elsewhere.
ILLUSTRATIVE WORKFLOW
From recording
to report
In a private transcription workflow, audio is captured through an approved recording process and processed by a speech-to-text model within the selected environment. The model is selected to meet the required transcription accuracy, including for fast-paced speech and a wide range of accents.
We map the flow from input to model processing, storage, output and connected applications. External APIs, supporting services and administrative access are included in that review.
This establishes which information stays within the selected environment, which connections are permitted and where additional controls are needed.
BEFORE PRODUCTION
Test the System Before Production.
Most organisations do not experience inefficiency as one obvious problem, otherwise they would probably fix it. Instead, inefficiency appears as dozens of small compensations.
1
Output Quality
Assess whether outputs meet the agreed requirement, where review is needed and what the system should not be used for.
2
Performance & Capacity
Validate response times, processing capacity and infrastructure requirements under the anticipated usage.
3
Access & Information
Check permissions, information flows and the controls around inputs, stored information and generated outputs.
4
Operational Readiness
Document the environment, dependencies and handover requirements, with responsibility for ongoing operation agreed before release.
For ongoing monitoring, maintenance and lifecycle decisions, the next step is AI Operations & Lifecycle.
Need to keep your AI
under your control ?
Bring us the task, the data constraints and the systems it needs to connect to.
We can help define a practical scope, choose the deployment approach and engineer the system around your environment.