Services
Advisory, engineering and operations for enterprise AI.
ByteForge provides advisory, engineering and operations services to organizations adopting agentic AI and products built on large language models. You may engage a service on its own or in sequence, up to a system we carry into production and operate after release.
Advise
Advisory services establish what to build, in what order and under what controls. They precede engineering work.
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AI Consulting & Strategy
Strategy, solution architecture and delivery planning that carry an organization from AI intent to a production roadmap.
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AI Readiness Assessment
An evidence-based judgment of the organization's capacity to adopt AI, prepared ahead of investment decisions.
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Data Strategy
A data audit, target architecture and governance plan that make AI initiatives feasible, defensible and repeatable.
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AI Governance & Compliance
Policies, controls, documentation and oversight aligned to the regulatory and standards frameworks that govern AI systems.
Build
Engineering services carry a defined scope from design through to a system running in production. We deliver each build into infrastructure the client controls and measure it against an agreed evaluation set throughout.
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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.
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Custom AI Development
Custom models and systems for requirements that standard approaches, hosted models and packaged software do not meet.
Operate
Operations services keep AI systems dependable after release and extend them into the platforms and workflows where the organization works. We run ongoing operations on a retainer.
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MLOps
Operations that keep models and agents measurable, reproducible and reversible for as long as they run in production.
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AI Integration & Implementation
Integration of AI systems into existing enterprise platforms with the security, identity and observability controls those platforms require.
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AI Business Automation
Governed agents that carry operational and administrative workflows, with defined decisions reserved for a person.
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Data Science & Analytics
Forecasting, anomaly detection, experimentation and decision analytics that give leadership a quantified basis for operational choices.
Engagement model
Scope, price and ownership are settled before engineering begins.
The sequence is the same whether the engagement ends with the review or continues into a build. Each stage settles a question before the next is undertaken, and quality is demonstrated by measurement throughout delivery.
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Consultation
The first conversation establishes the business objective, the systems involved and the constraints under which any solution must operate. We state whether the problem is one we are suited to address, and we share an indicative commercial range on that call so that the decision to proceed is informed.
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Architecture review, fixed scope
An architecture review, typically one to two weeks, examines the data, systems and requirements and results in a written design. From that design we fix the scope and the price. Where the design shows the system should not be built as envisioned, the review sets out the alternatives.
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Evaluation-led build
Evaluation sets are written before features and run continuously in CI, so every change is measured against the agreed standard. Progress is reported to the client's sponsors against those evaluation results at scheduled reviews. The client owns the code, model-provider accounts, data and infrastructure from the first week.
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Deployment, observation, handover
The system is deployed into the client's own environment and accounts with tracing on every step. We remain engaged through the first weeks of production, observing usage and correcting what evaluation did not anticipate. Handover is complete when the client's teams hold the operational documentation and can operate the system independently of ByteForge.
Common questions about our services
How do the services combine?
The services are designed as a sequence: a review establishes what to build, a build delivers it and operations keep it in service. Each stage produces the written artifacts the next depends on. Clients may also enter at any stage; where earlier work exists, the architecture review assesses whether it can be built on.
Can advisory work stand alone?
Advisory work is delivered as a complete engagement with its own deliverables and conclusion. An architecture review, readiness assessment, data strategy or governance engagement does not depend on a subsequent build with ByteForge. Each is documented so that an internal team or another supplier can act on the findings independently.
How does pricing work?
Reviews and builds are undertaken for a fixed price, settled when the architecture review concludes and the work is defined. Ongoing advisory and operations are provided on retainer. The cost of a build is therefore known before the organization commits to it, and leadership can judge whether the investment remains proportionate to the objective.
How does ByteForge work with an internal team?
We work alongside internal engineering, product and data teams and share the design, evaluation sets and monitoring with them from the outset. Internal engineers are invited into reviews, and the operational documentation is written for them. They work in the same repositories and environments as our team throughout delivery and can change the system independently at any point.
How is success measured?
Success is defined during the architecture review, ahead of the build: an evaluation set for the system and operational measures for the business outcome. The agreed evaluation set provides the measure of the system throughout delivery. The operational measures are specific to the workflow, such as cycle time, exception rate or cost per case, and are observed in production after release.
How does an engagement start?
An engagement starts with a call, which is most productive when an executive sponsor and a technical owner both attend. Useful preparation is a statement of the objective, the systems in scope and any constraints on data, vendors or timing. If the requirement is one ByteForge can serve, the next step is an architecture review, and a first system typically reaches production in about twelve weeks.
Begin with a scheduled call.
Describe the objective and the systems it affects. We will set out what an architecture review would examine and how it would proceed.