Generative AI Development

Text is the most mature area: drafting product descriptions, support replies, proposals and reports, summarising long threads, localising content, and rewriting copy for different audiences or reading levels. The pattern that works is generation from structured inputs - a product record, a ticket, a brief - with a reviewer approving output before it is published.

Images cover product imagery variations, marketing visuals, background replacement and concept work for design teams. Code generation powers internal developer tools, test generation and migration helpers. Document generation fills contracts, quotes and compliance packs from templates and data, where the model drafts the variable passages and fixed legal text stays locked. Each content type has its own quality bar, review needs and risks, so we scope them separately rather than as one generic AI feature.

Many needs are already met by packaged tools - writing assistants in office suites, image tools in design software, coding assistants in the IDE. If a packaged tool covers the task and its data terms are acceptable, buying is usually the right call. Custom development earns its cost when generation has to use your own data, follow your catalogue or house style, run inside your application or workflow, or produce output at a volume where per-seat tools become awkward.

A middle path is common: extend a platform you already use through its APIs or plug-ins, and build only the parts specific to you - the data connectors, templates, review screens and quality checks.

Generated content goes out under your name, so guardrails are part of the product. Inputs are screened for prompt injection and out-of-scope requests; outputs are checked against your style guide, banned terms, claims rules and tone, and for personal data that should not appear. Where content states facts - prices, specifications, policies - those facts are pulled from your systems rather than left to the model.

For public-facing output we add moderation for harmful or off-brand content and a review queue where editors approve, edit or reject drafts. Their edits are captured and used to refine prompts and checks, so the share of drafts needing heavy correction falls over time instead of staying flat.

Before launch it pays to settle a few questions with your legal team: which model provider terms apply to your inputs and outputs, whether a provider may train on your data, and whether image or code models carry indemnities or restrictions for commercial use. Open-weight models come with their own licences, some of which restrict certain uses or very large deployments.

On the technical side we keep provenance records - which model, prompt version and source data produced each output - and can attach content credentials metadata to generated images where your channels support it. Coding tools can be configured to flag suggestions that closely match public code. Copyright law on AI-generated material is still evolving, so we design for traceability rather than assume any single legal position.

Generic benchmarks say little about whether a draft is usable. We define quality in your terms: a rubric built from your style guide and acceptance criteria, scored by reviewers and by a grading model calibrated against them. In production the most honest signals are behavioural - how often editors accept a draft unchanged, how heavily they edit it, how often they discard it, and what happens downstream, such as fewer support follow-ups or faster quote turnaround. Tracking these per template and per model shows where to invest next.

Our dedicated developers use AI tools for the repetitive parts of the build: drafting prompt and template variants, generating synthetic test inputs and edge cases, scaffolding review-queue screens and API integrations, and writing documentation. The developer decides what to keep, reviews every change, and owns the parts that need judgement - guardrail logic, data handling and quality thresholds - so the generative AI feature you receive is built faster without being built carelessly.