AI where it earns its place.
Applied AI features, integrations and workflow automation — built around a defined task, measured against a baseline, and honest about the limits.
Engagement
Discovery, then build
Scope
Feature or workflow
Output
Integration & evaluation
Overview
Start with the task, not the model
AI is useful when it is attached to a specific job with a clear definition of done. We begin with that job: what the current process costs, where it fails, and whether a model actually improves it. Sometimes the answer is a simpler piece of software — and we will say so.
When AI is the right tool, the work becomes engineering: retrieval that grounds outputs in your data, guardrails for the failure paths, and evaluation that gives you evidence rather than a demo.
01
Measured against a baseline
Every use case is compared with the current process on accuracy, time and cost.
02
Designed for failure
Confidence thresholds, human review and fallbacks are part of the design, not an afterthought.
Capabilities
What this engagement covers.
Scope is agreed per project. The list below is the typical surface area, not a fixed package.
AI feature design
Scoping the task, choosing the approach, and defining success criteria before a line of integration code is written.
LLM integration
Server-side model integration with structured outputs, streaming where it helps, and provider abstraction that avoids lock-in.
Retrieval & grounding
Connecting models to your own documents and data with retrieval, citations and access rules that respect permissions.
Workflow automation
Replacing repetitive manual steps — classification, extraction, drafting, triage — with reviewable automation.
Evaluation & guardrails
Test sets, scoring and regression checks, plus input/output validation and prompt-injection defenses.
Cost & latency engineering
Caching, routing and model selection tuned to keep operating costs and response times predictable.
Process
How the engagement runs.
A sequence that keeps scope honest and progress visible from the first week.
- 01
Task selection
Identify a workflow with a real cost and a measurable outcome. Establish the non-AI baseline first.
- 02
Feasibility & risk
Review data availability, privacy constraints, failure impact and what 'good enough' actually means.
- 03
Prototype
Build the narrowest version that can be evaluated on real examples from your workload.
- 04
Evaluation
Score results against the baseline, document failure modes, and decide whether to continue, adjust or stop.
- 05
Production integration
Ship with guardrails, logging, cost monitoring and a human-review path for uncertain outputs.
Deliverables
What you receive.
Everything is written for the people who will use it — your engineers, your leadership and whoever operates the system afterwards.
- Use case definition with measurable success criteria
- Working integration in your application or workflow
- Evaluation set and results against the baseline
- Guardrails, fallback behavior and review path
- Operating notes covering cost, latency and known limits
FAQ
Questions worth asking.
Can AI handle our specific process?
Sometimes. It depends on the data, the tolerance for error and how the output is checked. We assess this on real examples before recommending a build.
Where does our data go?
Model providers, retention settings and data handling are agreed explicitly before implementation. Where required, we design around providers with suitable terms or keep processing on your own infrastructure.
Will this replace our team?
The realistic aim is removing repetitive work and speeding up drafts and triage. We design with human review for anything consequential.
Do you guarantee accuracy?
No credible engineer would. We measure accuracy on your workload, set thresholds, and design the product so uncertain outputs are visible rather than silently wrong.
Related
Often engaged together.
05
IT Consulting
Architecture planning, technical strategy and independent evaluation of technology decisions.
06
Cybersecurity Consulting
Security architecture, risk assessment and practical improvements aligned to how your team works.
07
Web Development
Modern responsive websites, business platforms and web applications with clean frontend engineering.
Have a scope in mind?
Tell us what you are working on and we will tell you honestly whether ai solutions is the right starting point.