Trusted by founders and growing teams

AI Assistants for Business

Secure, integrated AI assistants for support, operations, and customer workflows — built for real business processes.

We build AI assistants for business teams to automate support, onboarding, and internal operations with secure integrations and compliance-first data handling.

Our assistants are purpose-built for your data and workflows, with clear guardrails, auditability, and human handoff where it matters.

From customer support to internal operations, we integrate assistants into CRM, helpdesk, and product systems so teams can scale without chaos.

LLM Integration & RAG-ready Knowledge Bases

We connect assistants to your real data with safe LLM integration and retrieval pipelines that stay accurate and controlled.

Private knowledge bases with RAG and document retrieval
Secure data access, role-based controls, and audit logs
Structured responses grounded in policies and SOPs
Hybrid deployments for EU data residency needs

Need workflow automation beyond assistants? See AI workflow automationfor operations and process automation.

AI Assistant Capabilities

Customer Support Assistants

  • Automated responses based on available product documentation
  • Context-aware support using permitted user data, depending on system configuration
  • Multilingual reply support (e.g. DE/EN/ES/PL/RU)
  • Escalation rules & human handover
  • Integration with Zendesk, Freshdesk, HubSpot, WhatsApp

Internal Operations Assistants

  • AI agents for sales, HR, finance, ops
  • Knowledge retrieval over internal documents
  • Auto-generating emails, summaries, briefs, reports
  • Task automation (CRM updates, ticket processing, routing)
  • Slack/Teams/Email assistants for internal teams

Customer-Facing Assistants

  • Customer-facing help widgets and in-app assistants
  • Structured onboarding and self-service flows
  • Lead qualification and routing workflows
  • Product guidance with controlled, safe responses
  • Human handoff and escalation paths

Multi-Step Workflow Automation

  • Agents that perform sequences of tasks
  • CRM syncing, enrichment, lead scoring
  • Document parsing + PDF generation
  • Email sequences and follow-ups
  • Webhook-based automations and background jobs

Why Teams Choose Our AI Assistants

Secure integrations with CRM, helpdesk, and internal tools
Compliance-first data handling with EU hosting options
LLM workflows grounded in your policies and knowledge
Human handoff and escalation built in
Multilingual support for global teams
Production-grade monitoring and maintenance

When You Need AI Assistants

This service is ideal when you need:

AI support instead of large support teams
Agents that automate repetitive work
Assistants integrated deeply into CRM or operations
Smart FAQ/chat systems for websites or apps
A knowledge retrieval system across PDFs and documents
AI that understands your business, not generic replies
Workflow automation for sales, onboarding, HR, or legal

Tools & Technologies

LLMs & AI Stack

OpenAI, GPT-4.1/GPT-5 series, Llama 3, Mistral, custom local models

Search & Knowledge Base

Vector databases (Supabase, Pinecone, Qdrant), Embeddings, document chunking, structured retrieval

Frontend & UI

Next.js, React, chat widgets, custom UI components

Integrations

HubSpot, Pipedrive, Bitrix24, Zendesk, Intercom, WhatsApp API, Slack/Teams, Email automation tools, internal systems

Automation & Workflows

Node.js workers, queues, background jobs (Redis/BullMQ), Webhooks, CRMs, ERP systems, PDFs

Infrastructure

Vercel EU, Supabase EU, AWS EU, Docker, CI/CD

Process: How We Build AI Assistants

Step 1 — Knowledge & Data Audit

  • Document ingestion (PDFs, docs, sheets)
  • Product & process mapping
  • Role and scope definition

Step 2 — AI Architecture & Retrieval Setup

  • Vector DB and embeddings
  • Custom instruction tuning
  • Data routing, memory, context windows

Step 3 — Assistant Development

  • Chat logic, workflows, reasoning tools
  • Integrations with CRM or internal systems
  • User interface (web, Slack, WhatsApp, mobile)

Step 4 — Launch & Optimization

  • Human-in-the-loop review
  • Accuracy and safety tuning
  • Analytics, logs, usage insights
  • Ongoing iteration and model updates

Example AI Assistant Work (Case Studies)

AI assistant for a B2B company handling a significant portion of recurring support inquiries in this specific implementation

Context-aware support assistant with CRM integration and multilingual support

Internal sales agent updating CRM records and writing follow-up emails

Automated sales assistant with document parsing and email generation

Website assistant qualifying leads and routing them to sales calls

Lead qualification assistant with intelligent routing and CRM integration

Onboarding assistant explaining product usage in multiple languages

Multilingual onboarding assistant with interactive flows and knowledge base

Legal document assistant analyzing PDFs and summarizing key sections

Document analysis assistant with PDF parsing and intelligent summarization

FAQ

FAQ

Costs depend on scope, integrations, and data complexity. We provide fixed-scope options and retainers after a short discovery.

We use EU hosting options, access controls, audit logs, and data minimization based on your compliance requirements.

We integrate with CRM, helpdesk, and internal systems via APIs (HubSpot, Pipedrive, Zendesk, custom backends).

Yes — we build escalation paths to human agents and define safe fallback behavior.

Typical delivery takes 4–8 weeks depending on integrations, data readiness, and required workflows.

Related Articles

More insights and best practices on this topic

12 Dec 2025

AI in Real Products: What Actually Brings ROI in 2025

No hype. No demos. Just systems that make or save money. Learn where AI actually produces ROI in real products today—and why most AI initiatives fail after the demo.

12 Dec 2025

AI Automation vs Classic Automation: Where AI Is Overkill

And why 'smarter' is often worse than 'reliable'. Most business processes don't fail because they lack intelligence—they fail because they lack clarity, consistency, and ownership. Learn where AI automation delivers value and where classic automation is superior.

12 Dec 2025

How to Prepare Your Startup for Due Diligence (Tech Edition)

What investors actually look at—and what silently kills deals. Once interest is real, technical due diligence quietly decides deal quality: valuation adjustments, earn-outs, retention clauses, or a polite 'we'll get back to you.'

11 Dec 2025

Why 80% of AI Startups Will Die After the Demo Phase

In 2025, building an impressive AI demo is easy. Keeping it alive in a real product is not. Most AI startups don't fail because their models are bad—they fail because the demo works and nothing beyond it does.

AI assistants for business teams with secure integrations, compliant data handling, and operational reliability. Services are tailored to each system and requirements.

AI assistants operate on probabilistic models. Outputs may vary in accuracy and completeness and require human review, especially in operational, legal, or customer-facing contexts.