What we build / Generative AI
Generative AI that earns its place.
Copilots, content generation, and dynamic automation — we build generative features where they genuinely improve the product, with the evaluation and governance that keep them reliable. AI where it adds value, not as a gimmick.
Book a call →Generative AI in production
Generative features that hold up at scale.
Kenlo LYA generates contextual, human-quality replies to real-estate leads across WhatsApp and Meta — in production, at scale. PulseFit generates personalized fitness and meal plans per user, per session. Both have evaluation suites and live monitoring. Generative AI at Wegile is not a demo — it is an engineering discipline with quality gates.
Prompt engineering and evaluation
System prompts, few-shot examples, retrieval context, and output evaluation — designed together so generation stays reliable and on-brand, measured before launch.
Personalized generation at scale
Per-user, per-context generation that adapts to individual data and preferences — like PulseFit's AI plans that adjust to each user's goals, restrictions, and progress.
Omnichannel AI messaging
Generative AI responding across multiple channels — WhatsApp, Meta, web — with consistent persona, context handoff, and human escalation at the right moment.
Quality gates and drift monitoring
Every generative feature ships with an eval harness measuring output quality before launch. Post-launch drift monitoring alerts when quality degrades — not when users complain.
What we build
Generative features, engineered to be reliable.
Copilots & assistants
In-product assistants that actually understand your domain and your data.
Dynamic generation
AI that generates plans, content, and responses tailored per user, in real time.
Workflow automation
Generative steps embedded into real workflows, with human-in-the-loop where it matters.
Evaluation & safety
Quality gates, eval harnesses, and guardrails so output stays accurate and safe.
How we build it
AI-native delivery, governed by architects.
The same five-step delivery model behind every Wegile build. Not an AI wrapper — a production AI team.
Under the hood
Built for reliable generation.
Generative systems built with evaluation and governance so output stays accurate, safe, and on-brand.
Questions generative AI buyers ask us
Before you start. Straight answers.
Both. We build AI-native products from scratch with generative features designed in from day one. We also add copilots, content generation, and automation to existing products incrementally — using the same six-gate governance pipeline regardless of the starting point.
Evaluation suites — labeled test sets that measure output quality against your accuracy and tone criteria before any merge. We establish your quality baseline during the build, then monitor for drift after launch. This is engineering, not just prompting.
Yes, with the right architecture. Human-in-the-loop checkpoints, output filtering, confidence thresholds, fallback to deterministic responses, and a full audit trail. We've built AI features in fintech, health, and enterprise contexts where reliability is non-negotiable.
We build with fallback chains — when a model is unavailable or returns an unexpected output, the system degrades gracefully rather than failing. We monitor model behavior post-launch and respond to changes before they affect users.
Yes. Generative features can be added to existing backends and mobile/web frontends incrementally. We scope the integration point, architect the AI layer into the existing system, and ship with full governance. No big-bang rewrite required.
Have a generative idea? Let's make it production-ready.
Response within 24 hours. After the architecture call, a named pod and day-one plan arrive within 4 business hours.