Frequently asked questions

Answers for procurement, IT, and business owners evaluating AI automation.

What types of companies do you work with?
Mid-market and enterprise companies, CRM/ERP integrators, and software houses that need production AI delivery under NDA — not one-off chatbot demos.
Do you sign an NDA before the first call?
Yes. NDA is standard before sharing architecture, data samples, or internal documentation.
Can you deploy on-prem or in a private cloud?
Yes. We support on-prem, isolated VPC, Yandex Cloud, Selectel, and Cloud.ru — data stays in your perimeter.
What is a typical project budget?
Audit from €1,500. Implementation from €5,000. Typical enterprise deals are €25k+. We quote fixed scope before development starts.
How long does implementation take?
Audit: 1–2 weeks. MVP: 2–4 weeks. Full production rollout: 4–12 weeks depending on integrations and compliance requirements.
Do you work with amoCRM, Bitrix24, and 1C?
Yes. CRM/ERP integrations are a core competency — bidirectional sync, webhooks, document flows, and error handling with retry.
When does AI actually make sense?
When manual work is repetitive, documents are unstructured, or support volume is high. We start with ROI calculation — not technology hype.
What LLM providers do you use?
Claude, OpenAI, YandexGPT, GigaChat — selected per compliance, language, and cost. Client can own API keys and infrastructure.
What is RAG and when do you recommend it?
Retrieval-Augmented Generation connects an LLM to your documents. We recommend RAG for support, sales enablement, and internal knowledge bases.
Do you build AI agents or just chatbots?
Both — but we focus on agents that take actions: update CRM, generate documents, trigger workflows, escalate to humans.
Can you integrate with n8n or existing automation?
Yes. We extend n8n, Zapier, or custom workflows with AI layers and API integrations.
How do you handle GDPR and 152-FZ?
DPA, consent flows, retention policies, and architecture review before go-live. Russian deployments follow 152-FZ requirements.
Do you provide SLA and monitoring?
Yes — optional post-launch support with monitoring, alerting, iteration backlog, and response time agreements.
Who owns the code and IP?
Client owns deliverables per contract. We hand over repositories, documentation, and deployment runbooks.
Do you offer white-label for integrators?
Yes. Partners face the client; we deliver under NDA with documentation for your PM and engineers.
What does the first engagement look like?
30-minute discovery call → AI & Automation Audit → fixed roadmap and estimate → phased implementation with milestones.
Can you rescue a failed AI pilot?
Often yes. We audit architecture, data quality, and integration gaps, then rebuild for production with measurable KPIs.
Do you support voice AI and call centers?
Yes — speech-to-text, voice bots, and CRM logging for inbound/outbound call workflows.
What about OCR and document processing?
OCR pipelines for invoices, contracts, and scans with field extraction and export to 1C, CRM, or ERP.
Can you deploy Open WebUI or self-hosted LLM?
Yes. Self-hosted stacks with Open WebUI, private models, guardrails, and SSO for internal teams.
What is MCP and do you implement it?
Model Context Protocol connects LLMs to tools and data sources. We build MCP servers for CRM, databases, and internal APIs.
Do you use LangGraph for agents?
Yes, for multi-step agents with state, human-in-the-loop, and observability — when complexity exceeds simple chains.
How do you measure ROI?
Baseline manual hours, error rates, and conversion metrics before launch. We report deltas after 30/60/90 days.
What industries have you delivered in?
Cybersecurity (Kaspersky), B2B sales, government affairs monitoring, education, banking media, and integrator subcontracting.
How fast do you respond to new requests?
Within 4 business hours. Preliminary scope and estimate within 24 hours after the discovery call.

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