6–13 specialized AI agents (6 in Small · 9 in Medium · 13 in Large) on a unified platform + Lavatti Moderator School: a continuous training and certification system for our moderators who work with your community. This is not a tool — it is an operating system. Technology and People: inseparable.
Your community data builds the Knowledge Base. That same KB works simultaneously in two directions: AI Engine (13 agents work from the KB in real time) and Lavatti Moderator School (training materials, exams, and quizzes are built on real cases from the KB). Not two parallel products — two layers of one system.
/help command. The system itself sees that a member is inactive for 14 days and sends a personalized DM — without a command, without delay.DeFi protocol, 3,400 members in Discord and Telegram. Two moderators spent 3–4 hours/day on questions like "how to connect a wallet", welcoming newcomers, and cleaning up spam. The server wasn't patrolled at night — in the morning the team found 50–80 unresolved messages.
After deploying Lavatti Community OS (14 business days):
* Your numbers are calculated in the first month of the audit.
Can one smart agent do it all? No. The Support Agent knows only your Knowledge Base — it cannot ban. The Moderator Agent knows only the rules — it doesn't answer product questions. This is an architectural decision, not a limitation. Each agent sees only the necessary context: less context → fewer errors → clear accountability and an audit trail for every action.
Members get an answer from your FAQ in 8–15 sec — at any time. If uncertain — it passes the question to a human rather than guessing.
Spam, scam links, toxicity — removed before other members see them. You set the rules, the agent enforces them 24/7.
Every newcomer gets a personalized welcome with their name, a role, and an explanation of the rules. No one gets lost or silently leaves after 5 minutes.
RU · EN · ES · ZH · and any other — every member gets an answer in their own language from a single KB. Auto language detection, no list setup required. Responds in the member's language automatically, without delay. Phase 3 priority markets: Latam (ES/PT), SEA (VI/TH), Turkey (TR).
Every week — a report: which questions are asked most, what concerns members, where activity is dropping. Data for your decisions.
Conflict, legal question, ambiguous situation — the agent immediately notifies the right member of your team. Nothing gets lost.
A self-deployed bot sees every message as the first one. Lavatti remembers every member's history from day one.
We analyze your platforms: message volume, types, bottlenecks. We create a KPI baseline and automation plan.
We configure the system on your content. Load the KB. Test 50+ scenarios. Train the team on the dashboard. 30 days in production.
If the results meet expectations — standard terms. If not — full export of your data. Exit terms are fixed in advance.
| Task | Lavatti AI | Your team |
|---|---|---|
| Answers to standard questions (FAQ) | ✓ Automatically | Rarely <20% |
| Spam and toxic content | ✓ Instantly | Complex cases only |
| Onboarding new members | ✓ Every member | Strategic decisions |
| Night duty | ✓ 24/7 | Not needed |
| Complex conflicts, legal issues | → Escalates | ✓ You decide |
| Complex escalations — receives full AI summary | → Hands off | ✓ Moderator decides |
| Community strategy + growth | — | ✓ Your team + Lavatti |
| Rules and KB updates | — | ✓ You control |
| Community audit, platform analysis | PM | 4–8h |
| VPS, stack (n8n, Qdrant, Redis, PostgreSQL, Docker) | DevOps | 24–36h |
| 13 agents — workflow, logic, integrations | n8n Developer | 56–84h |
| Prompts for all 13 agents | AI Prompt Engineer | 30–48h |
| LangGraph StateGraph — full architecture (Python) | AI Prompt Engineer | 34–52h |
| OpenViking Context Engine — deploy, configure, integrate | DevOps | 12–18h |
| Knowledge Base — up to 5 languages | KB Editor | 48–72h |
| GPU server + hybrid LLM router (70/30) | DevOps | 24–36h |
| Client dashboard (Supabase) | n8n Developer | 8–12h |
| Monitoring — Grafana + Netdata + alerts | DevOps | 16–24h |
| QA — load, multilingual, GPU pipeline | QA Engineer | 20–28h |
| Client documentation | PM | 8–12h |
| Knowledge Base updates (4× /month, all languages) | KB Editor | 8–14h |
| Prompt tuning + GPU model optimization (weekly) | AI Prompt Engineer | 3–5h |
| LangGraph StateGraph — graph logic monitoring, Python agent updates | AI Prompt Engineer | 1–2h |
| GPU monitoring + latency audit (weekly) | DevOps | 1–2h |
| OpenViking Context Engine — agent memory monitoring, pruning | DevOps | 0.5–1h |
| Reports + 4 meetings/month | PM | 5–8h |
| Quality spot-check (~10% traffic) | KB Editor | 1–2h |
| Workflow audit / execution logs | n8n Developer | 0.5–1h |
| Escalation handling (20–50 per month) | KB Editor | 3–6h |
| Incident resolution (GPU + cloud) | DevOps | 2–4h |
| Regression QA (GPU, multilingual, load) | QA Engineer | 3–4h |
| Agent workflow updates | n8n Developer | 2–4h |
| Client dashboard (Supabase) — metrics, KPIs, query optimization | n8n Developer | 3–5h |
| Stack/dependencies — Docker, n8n, Qdrant, GPU stack patches | DevOps | 1–2h |
| Platform integrations — API updates, token rotation (6 platforms) | n8n Developer | 1–2h |
The platform runs 24/7 with auto-monitoring and alerting (Grafana + PagerDuty). If you need faster response from the Lavatti team or a dedicated manager — add a package:
| Package | What's included | Price/mo |
|---|---|---|
| Standard SLA | Telegram channel with Lavatti + KB updates on request, Lavatti response within 4h | $200 |
| Extended SLA | Dedicated Lavatti manager + monthly analytics session, response within 1h | $500 |
| Priority SLA | Dedicated manager + monthly analytics + priority KB and agent updates | $1,200 |
Payment on signing: $2,000 implementation + $299 first month. System goes live in ~10 business days. Over 30 days we count real Active Members — this confirms the tier. We build three KBs, test 50+ scenarios, train the team.
After month 1 the tier is locked based on real AMs. The dashboard shows monthly dynamics. Normal fluctuations of ±10–15% are activity variance, not a signal. What matters is a sustained trend, not a one-off spike.
Moving to a higher tier isn't "flipping a switch for more capacity." New agents are built for your data from scratch: trained on your KB, tested on your scenarios, deployed in parallel with zero downtime. Here's what you're paying for:
Not happy with results after month 1 — we part ways. All your data (history, KB, settings, moderation policy configurations, and agent routing logic) is exported in standard formats (CSV / JSON / YAML). Exit terms are fixed in the contract in advance. Note: implementation fee is non-refundable — it covers work already delivered.
Lavatti acts as your technical agent. All provider accounts — VPS (Hetzner), AI API (Anthropic), database (Supabase), GPU (RunPod if applicable) — are created under your company's name. Lavatti signs up and configures them on your behalf; you own them from the first day.
This means no lock-in: you can hand over management to another team at any time, and all infrastructure stays with you.
During the contract you receive view-only access to all services — dashboards, logs, analytics. Lavatti holds admin rights and is solely responsible for security under the contract. This protects you: if something breaks, the liability sits with Lavatti, not with your team.
Full admin rights transfer to you upon normal contract completion — along with all credentials, runbooks, and configuration documentation.
If the contract ends early — for any reason, including force majeure or issues on Lavatti's side — you can immediately rotate all provider keys yourself. Since accounts are in your name, you have this right at any moment.
Once Lavatti's access keys are revoked across all providers, the contract is formally closed. The system keeps running under your control. This mechanism is fixed in the contract in advance.
Your community's Knowledge Base is the shared foundation for agents and moderators. Agents use the KB in real time. Lavatti trainers use real cases from the KB to build training materials, quizzes, and School exams.
YouTube, Instagram, TikTok — planned expansion. Platform count is determined by tier: Medium includes 3 platforms; Large includes 6. Not available in Stage 1 (Small).
The Translation Agent already works in any language. Phase 3 is active targeting of three high-potential crypto markets: custom KB sections, adapted tone-of-voice, and regional analytics dashboards.
Community OS goes on-chain. Agents see not only activity in messengers — they know who is a holder, who is a whale, who sold. Member reputation is built from two sources: Discord/Telegram + wallet.
Works if you have an active community on at least one platform (Discord, Telegram, X, YouTube, Instagram, TikTok) and have product documentation or a FAQ — even a rough draft. The Small tier starts from day one — the system works even with 50–100 Active Members and grows with you. Not a fit: closed corporate groups without user communication and projects without a single product document. If unsure — a call will show.
Bots react to commands (/help). Lavatti Community OS acts independently and learns from your content — sees spam and removes it, sees a question and answers it, sees a newcomer and welcomes them. Without a command. This is a different class of solution.
Support Agent answers only from your KB. Confidence <60% — it escalates to a human, it doesn't guess. You control the knowledge base and see all responses in the dashboard. No confidence — no answer.
Upon any termination — full export of all data: History, KB, analytics, moderation policy configurations, agent routing logic. Everything in standard formats (CSV / JSON / YAML). Your data — always yours. Contractually guaranteed.
You can. It'll take 3–6 months: integrations with three platforms, a Knowledge Base with semantic search, OPA policies, AI orchestrator, monitoring, retry logic. Our solution is ready in 10–21 days — and we maintain it.
Moderator Agent by default only bans at high confidence. Borderline cases go to the escalation queue for your team. Reaction levels (warning / mute / ban) and confidence thresholds are configured by you during implementation.
$299/mo — fixed all-inclusive price, including LLM-API costs (OpenAI, Anthropic). No separate invoices for tokens. Possible optional costs: KB content preparation ($300–800 one-time — only if you have no existing documents), Lavatti support packages ($200–1,200/mo), and external system integrations ($500–2,000 one-time; included in Medium and Large implementation). Implementation — one-time. Audit — in month 1.
That's exactly why there's no universal bot. During implementation we load your FAQ, rules, specific terms, product documentation. Support Agent answers from your KB — not a generic one. The more accurate the materials, the more accurate the AI. The audit will show what to prepare.