AI
AI systems
Assistants and retrieval pipelines wired into places your team already works — not slide-deck demos.
Capabilities
We build internal copilots, customer-facing assistants, and moderation aids with retrieval over your docs, Notion, or ticket history. Tools are grounded with citation-friendly chunks so answers stay auditable — important when AI-SEO and support overlap.
Workflow agents trigger from Discord events, form submissions, or cron via n8n/Make when you need human approval gates between steps.
Commercial guardrails
Every AI scope lists data retention, model vendor, and fallback behavior when APIs fail. We refuse black-box bots that invent policy for regulated products without review checkpoints.
Example from delivered work
Telegram verification system — Deterministic automation first; AI layered only when rules need fuzzy matching.
Straight answers
Do you train custom models?
Most clients need orchestration and retrieval, not fine-tuning. We recommend fine-tunes only when evaluation sets prove ROI. Otherwise hosted models with strict prompts and tools win on time-to-value.
How does AI-SEO relate to your AI work?
Marketing pages include FAQ blocks and schema so generative engines can cite you. Product AI is separate — both benefit from clear entity naming and consistent facts across your site.
Can AI access our customer PII?
Only under your written data map. Privacy standards on our ethics page apply to embeddings storage and vendor subprocessors.
What is a realistic timeline?
Pilot assistants often ship in two to four weeks with a defined knowledge corpus. Enterprise governance adds discovery time we quote separately.
Scope engineering with us
Reference this page in Discord so we know which technical lane you need.
2 spots · Q2 2026 · Escrow-ready · Same-day replies on Discord