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Custom AI Development
Custom models and systems for requirements that standard approaches, hosted models and packaged software do not meet.
About Custom AI Development
A general-purpose model or an available product does not serve every requirement: unusual data modalities, strict latency or cost envelopes, on-premises constraints or proprietary domains. Custom AI development addresses these cases with purpose-built models, pipelines and systems, combining techniques from more than one discipline where the requirement calls for it. We record constraints on data residency, hardware and latency as requirements before selecting any model.
A custom system has no vendor to maintain it, so we design it for the organization's own engineers to maintain. The design therefore provides reproducible training and inference pipelines, documented data dependencies and a defined retraining process. Training, where required, runs on pipelines those engineers can rerun after handover. We version each pipeline with the data and configuration behind a given model, so you can rebuild any model.
What you receive
- Requirement specification and constraint analysis
- Purpose-built model and training pipeline
- Evaluation set specific to the requirement
- Deployed system with operational documentation
When to engage
Engage once you have tested the requirement against available models and products and none of them meets it.
More in Build
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AI Product Development
End-to-end delivery of an AI-enabled product, with a single supplier accountable for its release.
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Agentic AI Systems
Autonomous and supervised agents that plan and execute actions across tools and systems.
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LLM Development
LLM application engineering: retrieval-augmented systems, fine-tuning, prompt and tool architecture, and the evaluation that measures them against requirements.
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Generative AI
Text, image, audio and code generation features, released with evidence that their output meets the standard set for them.
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Reinforcement Learning
Learned decision policies for operational problems in which each choice changes the options available for the next.
Discuss this service on a call.
Describe the objective and the systems it affects, and we will outline how an engagement would proceed.