Prepared data, a versioned model and a connected application.
DATA / MODELS / OPERATIONS
AI platforms
Connect data, training and inference with version control, budgets and recovery.
- From datasets to APIs
- Training with limits and recovery
Wendelmaques · Infrastructure consulting
AI in production.
Infrastructure from planning to operations, priced by proposal.
- 12+ years in engineering
- Software, telecom and system operations
- AI, data and speech
- Platforms, sensitive data and existing systems
- Work directly with me
- Review, deployment and ongoing operations
Areas of expertise
Implementation experience applied to your company's challenges. Explore technical decisions and the scope you can engage me for.
Protected sources, limited access and an output subject to review.
ACCESS / EVIDENCE / AUDIT
AI with sensitive data
Permissions, protected storage and output reviewed by people.
- Backend authorisation
- Source checks enforced by code
Existing systems, staged requests and confirmation before action.
INTEGRATION / CONTINUITY
AI in existing systems
Integrate with databases, applications and telephony in stages that preserve operations.
- APIs, events and existing databases
- Speech and telephony
The queue organizes models sharing the same GPU.
GPU / ORCHESTRATION
Shared GPU
Coordinate GPU use across text and speech models.
- Coordinated model use
- Capacity and waiting-time assessment
The application accesses the model on infrastructure defined for the project.
LLM / vLLM
Private inference
vLLM connected to a product, with memory and concurrency limits.
- Capacity planning
- Access control and operations
Audio and text follow the sequence of the same conversation.
WEBRTC / OPUS / WHISPER
Speech operations
Real-time audio, transcription and processing recovery from browser to server.
- Capture by participant
- Durable audio and queue recovery
Consulting for every stage of operations
From an architecture assessment to ongoing operations. Scope and pricing are defined for your product, data and team.
Map the architecture and bottlenecks before defining the deployment.
Infrastructure review
Map data and integrations, identify bottlenecks, assess capacity and plan deployment.
Quoted per project
Request a proposal
Connect infrastructure to the application and check the integration.
Deployment
A data and model platform, private inference, speech and integration with your systems.
Quoted per project
Request a proposal
Monitor the service and keep a defined recovery path.
Ongoing operations
Monitoring, updates, recovery, capacity planning and cost control.
Monthly engagement, quoted
Request a proposalConcept illustrations generated with AI.
From assessment to operations with your team
Scope, responsibilities and acceptance criteria agreed before deployment.
- Assess the workload
Product, data, volume, latency and budget.
- Measure and deploy
Validate the real workload, integrate and document operations.
- Maintain operations
Monitor failures and costs, tune capacity and rehearse recovery.
Product workload guides capacity.
Concept illustration generated with AI.Reading and experience
Articles
Browse articles · 20 articlesAI in production: what you need beyond the model
Queues, access and recovery are part of the service.
Concept illustration generated with AI.A deployment guide for companies: real workloads, APIs, queues, access, monitoring, versions and recovery.
Experience
Wendelmaques
12+ years in engineering
AI platforms, sensitive data, real-time audio and integration with existing systems.
Consulting
Let's assess your project
Describe your product and challenge. I reply with scope and a proposal.
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