Every engagement starts with clarity on scope. The Audit gets you there — then the right next step becomes obvious.
The Audit is where every engagement starts. Before any code is written, before any architecture is designed — we spend two focused weeks understanding your operations, mapping your processes, and identifying where AI will and won't create real value.
The output is a written deliverable: a prioritised build roadmap with fixed-fee implementation estimates for each opportunity, ranked by impact and feasibility. You can take it anywhere — implement with us, take it in-house, or hand it to another team. No dependency, no obligation.
Structured conversations with your operational leads to map actual workflows — not org charts or aspirational process diagrams.
Visual documentation of your core operational flows, with manual touchpoints, decision points, and data sources identified.
Each opportunity evaluated against technical feasibility, data readiness, and estimated ROI. We include opportunities that won't work, not just ones that will.
A ranked list of AI projects ordered by impact and implementation effort — with a recommended sequencing and rationale for each decision.
Concrete cost estimates for each prioritised project, covering development, infrastructure, and ongoing model costs — ready to take into a budget conversation.
// Who it's for: US businesses with established operations, at least $1M in annual revenue, and at least one process that currently involves significant manual effort. You do not need to know where AI fits — that is what the Audit determines.
Every Sprint starts from a defined scope — usually the prioritised output from your Audit. We price against the scope, not against time. You know the number before work begins.
AI systems vary enormously in complexity — a basic LLM integration and a production-grade multi-agent system are different orders of magnitude. We do not publish upper limits because they would either mislead you or constrain us. What we do publish is a minimum: $10,000. Below that, we cannot deliver production-quality work.
The fee, the scope, and the deadline are agreed in writing before the Sprint starts. Scope creep does not happen — if requirements change, we scope and price the change separately before building it.
A production-deployed system, full source code ownership, technical documentation, and a handover session with your team. We do not leave you with a system you cannot operate without us.
// Who it's for: organisations that completed an Audit (with us or internally) and have a clearly defined AI project ready to build. Also suitable for organisations with an existing technical spec or detailed requirements document.
The Sprint is the build. A focused, fixed-scope engagement that takes a defined AI project from design to production deployment. No open-ended retainers, no scope drift — a start date, an end date, and a delivered system.
Sprints typically run 4–12 weeks depending on complexity. Throughout the build, you receive weekly progress updates and staged delivery milestones — so you are never in the dark about where the project stands.
Larger, more complex AI systems that go beyond a single sprint. Custom builds are scoped individually — every engagement is different, and pricing reflects the specific system being built.
Multi-step autonomous agents that handle complex, context-dependent tasks — research synthesis, automated triage, intelligent routing, outbound workflows. We design the agent architecture, tool set, and failure handling from the ground up. Production reliability is built into the design, not bolted on afterward.
Deep dive: AI Agent Development ↗Embedding language model capabilities into your existing software stack — CRM, ERP, internal dashboards, communication tools. We write the integration layer, handle prompt architecture, manage context and token budgets, implement caching strategies, and build the monitoring and fallback logic that production systems require.
Deep dive: LLM Integration ↗Retrieval-Augmented Generation pipelines that give AI access to your proprietary data — internal documents, product databases, historical records, unstructured knowledge bases. We handle ingestion, chunking strategy, embedding pipeline, vector store selection, retrieval tuning, and answer quality evaluation. The result is a system that answers accurately from your data, not from general training.
Deep dive: RAG Systems ↗AI-powered pipelines that replace high-volume manual processes — document extraction and classification, data transformation, quality review, intelligent routing, multi-step approval flows. We map your current process in detail, identify every automation point, and build the replacement end-to-end. Includes integration with your existing tools and systems.
Deep dive: AI Workflow Automation ↗For organisations that need a board-ready AI strategy before committing to implementation. We assess your current data infrastructure, competitive landscape, internal capability, and risk posture — then produce a written strategic roadmap with prioritised initiatives, build-vs-buy recommendations, and a phased implementation timeline. This is distinct from the Audit, which focuses on specific process opportunities.
For organisations evaluating an AI vendor, acquiring a company with AI assets, or assessing an internally built AI system before scaling it. We review architecture, model choices, data pipelines, security posture, and operational risk — and produce a written assessment with a clear verdict on what is solid, what needs remediation, and what represents material risk.
Production AI systems are not set-and-forget. Models change, usage patterns shift, edge cases surface, and new opportunities emerge once a system is running at scale. The retainer keeps your AI infrastructure improving rather than stagnating.
Retainers are available to organisations with a production AI system already in place — whether built by Mason Bedford or by another team. We take a monthly look at performance, identify degradation or drift, and implement targeted improvements.
A structured assessment of system performance — output quality, latency, error rates, cost per operation, and user satisfaction signals. We surface degradation before it becomes a problem.
Ongoing refinement of prompts, retrieval parameters, and context strategies as usage patterns and model behaviour evolve. Includes responding to model version changes from your AI provider.
Analysis of failure cases and unexpected outputs, with targeted fixes to the prompt layer, retrieval logic, or system architecture as needed. We track what breaks and why.
When you are ready to extend the system — add new capabilities, integrate additional data sources, or automate adjacent processes — we scope and estimate the next build within the retainer.
Retainer clients get priority scheduling for new Sprint work. When you are ready to expand, you do not go to the back of the queue.
A side-by-side overview of how each engagement type is structured.
| Criteria | AI Audit | Implementation Sprint | Bespoke Build | Optimisation Retainer |
|---|---|---|---|---|
| Fee structure | $998 fixed | Fixed, scoped per project — from $10,000 | Fixed, scoped individually — varies by complexity | From $2,000/month, cancel anytime |
| Timeline | Quick turnaround | 4–12 weeks typical | Defined at scope stage — varies | Ongoing monthly engagement |
| Scope definition | We define it during discovery | Agreed in writing before work begins | Co-developed during scoping phase | Defined monthly at performance review |
| Output | Written roadmap and estimates | Production-deployed AI system | Production-deployed system + documentation | Monthly performance report + implemented improvements |
| Best for | Organisations that don't yet know what to build or where AI fits | Organisations with a defined scope ready for implementation | Complex, multi-component systems requiring custom architecture | Organisations with production AI that needs ongoing improvement |
| Prerequisite | None — this is the starting point | Defined scope (from Audit or existing requirements) | Initial scoping session with Mason Bedford | Existing production AI system |
Fill in the enquiry form and describe your situation. We will tell you which engagement type fits and why — no pressure to start with anything you do not need.