AI consulting from strategy to a working system.

Gyde helps enterprise teams choose where to invest, set the operating rules and build AI systems that work inside real business processes.

Talk to an AI architect See our approach
One connected stack Representative scope

Experience to evaluation

We work across the layers that determine whether AI creates a dependable business outcome.

Apps & workflows Routing Inference Fine-tuning Evals
01Business workflow first 02Production engineering 03Governance by design

Strategy and governance

Start with the decision that is blocking progress.

Use an advisory path when the company needs direction, ownership or governance before a delivery scope is ready.

A1

AI Strategy Consulting

Choose the business priorities, compare use cases and issue a funded roadmap with named owners.

Explore this path A2

Enterprise AI Governance

Set risk tiers, decision rights, controls and evidence records for the live AI portfolio.

Explore this path A3

Fractional Chief AI Officer

Bring in a part-time executive to own strategy, portfolio decisions, governance and leadership reporting.

Explore this path

The capability stack

Five consulting capabilities across the AI delivery lifecycle.

Enter at the layer where your system is constrained. Each engagement connects to the application, assigned owners, operating procedures, and measurable results required around it.

01

Apps & Workflows

Design AI applications for repeatable processes, with defined data access, actions, review points, and ownership.

Explore capability 02

Routing

Choose the right model for each request based on quality, latency, cost, and policy.

Explore capability 03

AI Lab Infrastructure

Plan, commission, and operate private GPU infrastructure and open-model services for defined enterprise workloads.

Explore capability 04

Inference

Benchmark, deploy, and operate models on owned, cloud, or sourced GPU capacity.

Explore capability 05

Fine-Tuning

Adapt models to specialised behaviour when prompting and retrieval no longer close the gap.

Explore capability 06

Evals

Define evaluation criteria, test representative cases, and connect results to release decisions.

Explore capability

How we think

Engineering choices follow the operating reality.

01

Define the job

Specify the workflow, decision, user, and unacceptable failure before choosing a model or architecture.

02

Build the control plane

Permissions, evaluation results, fallbacks, and human ownership are included in the initial product scope.

03

Support the next investment

Each engagement ends with working software and measurable results for a clear scale, change, or stop decision.

The engagement

Each phase answers a production question.

The initial scope is narrow. Each phase produces working software and a reviewable deliverable for the next decision.

1

Discover

Frame the opportunity

Align the workflow, baseline, constraints, owners, and production success measures.

2

Design

Choose the intervention

Decide what belongs in workflow, retrieval, routing, inference, tuning, and evaluation.

3

Deliver

Build the first workflow

Ship the smallest complete system that exercises representative data, controls, and integrations.

4

Decide

Review results before expansion

Evaluate quality, adoption, risk, performance, and economics before expanding scope.

Bring a defined business constraint

Tell us where your AI system is stuck.

We will help frame the smallest credible path from the current constraint to a production outcome.

Discuss your AI system