AI Assistants
Task-specific assistants that draft, summarize, classify and answer using your own data.
Benefit — Skilled staff stop doing first-draft work.
For: SaaS, agencies, support teams
AI &
Automation.
We design, build and operate AI assistants, automation pipelines and internal AI tools that remove manual work from your business — safely, measurably, and with humans in control.
Scoped in writing before development
Milestone-based invoicing
Production-grade, monitored systems
Overview
Automation that executes real work.
What it means
AI & Automation is the engineering of systems that perform work — reading documents, answering questions, routing requests, moving data between tools — without a person driving every step.
Our approach
We automate processes, not job titles. Every system starts from a mapped workflow, keeps a human review gate where errors are costly, and is instrumented so you can see exactly what it did and why.
Business value
Hours of repetitive work removed per week, faster response times, fewer manual errors, and operational knowledge captured in systems instead of individual heads.
Typical use cases
Support triage and drafting, document intake and extraction, CRM hygiene, internal knowledge assistants, reporting pipelines, and cross-tool workflows orchestrated with n8n.
Business challenges
The problems this service removes.
Most automation projects start from the same operational pains. If several of these sound familiar, there is measurable value on the table.
- +Repetitive manual work eating skilled hours
- +Slow internal processes and approval chains
- +Poor customer response times
- +Data scattered across disconnected tools
- +Expensive operational overhead
- +No automation between core systems
- +Human errors in copy-paste workflows
Our solutions
What we build.
Workflow Automation
n8n and API-based pipelines connecting your tools into zero-touch processes.
Benefit — Swivel-chair work removed end to end.
For: SMEs, operations teams
Document Processing
Automated intake, extraction and validation of invoices, forms, contracts and reports.
Benefit — Hours of data entry per week eliminated.
For: Finance, healthcare, manufacturing
Internal Knowledge Bases
RAG systems over your documentation, policies and history — with sourced answers.
Benefit — Institutional knowledge becomes searchable.
For: SaaS, education, enterprises
Customer Support Automation
Triage, drafting and escalation workflows with human review gates.
Benefit — Faster responses without losing quality control.
For: E-commerce, SaaS, travel
AI Chatbots
Grounded, on-brand chat for websites and internal portals — no hallucinated answers.
Benefit — 24/7 first-line answers from your real content.
For: E-commerce, hospitality, education
CRM Automation
Lead enrichment, deduplication, scoring and follow-up sequences kept in sync.
Benefit — A CRM your team can finally trust.
For: Agencies, sales teams
Email Automation
Classification, routing, drafting and follow-ups driven by real mailbox context.
Benefit — Inbox time cut without dropped threads.
For: SMEs, service businesses
AI Content Pipelines
Structured content generation with editorial review, publishing and SEO steps built in.
Benefit — Consistent output at a fraction of the effort.
For: Marketing teams, publishers
Business Process Automation
End-to-end automation of quoting, onboarding, reporting and compliance processes.
Benefit — Processes that run the same way every time.
For: SMEs, manufacturing, finance
MCP Integration
Model Context Protocol servers that let AI tools operate your internal systems safely.
Benefit — AI that acts on your stack, with guardrails.
For: Engineering teams, SaaS
n8n Automation
Design, hosting and maintenance of production n8n instances and workflow libraries.
Benefit — Self-hosted automation you fully own.
For: Agencies, SMEs
Custom AI Applications
Bespoke AI products — from internal tools to client-facing features — built end to end.
Benefit — Capabilities your competitors can't buy off the shelf.
For: Startups, SaaS, enterprises
Industries
Where automation pays off.
Agencies
Client reporting, content pipelines, CRM hygiene and white-label automation delivered under your brand.
SaaS
In-product AI features, support automation and internal ops tooling that scales with your user base.
E-commerce
Order-issue triage, product data enrichment, review handling and customer-service drafting.
Healthcare
Document intake, appointment workflows and admin automation — with strict data-handling boundaries.
Education
Enquiry handling, enrollment workflows and knowledge assistants over course material.
Travel
Booking-change automation, itinerary generation and multilingual customer communication.
Finance
Invoice processing, reconciliation workflows and report generation with audit trails.
Hospitality
Reservation handling, guest communication and review-response automation.
Manufacturing
Order intake, supplier communication and production-reporting pipelines.
Technologies
Tools chosen per problem, not per hype.
Anthropic Claude
Primary model for reasoning-heavy work: long documents, complex instructions, reliable structured output.
OpenAI
Broad model family and embeddings — used where its ecosystem or price/performance fits the task.
Gemini
Multimodal and long-context workloads, and clients standardized on Google Cloud.
MCP
Open protocol for connecting AI models to your internal tools and data with controlled permissions.
n8n
Self-hostable workflow engine — you own the automation layer instead of renting it per task.
LangChain
Orchestration of multi-step AI pipelines where chains, tools and retries need structure.
Ollama
Local model serving for privacy-sensitive workloads that must never leave your infrastructure.
Node.js / NestJS
Our standard backend for APIs, webhooks and integration services around the AI layer.
Python
Data processing, evaluation harnesses and ML-adjacent tooling.
PostgreSQL
System of record plus pgvector for embeddings — one database, fewer moving parts.
Redis
Queues, caching and rate-limiting that keep automation pipelines fast and well-behaved.
Docker
Every system ships containerized — reproducible deployments on your infrastructure or ours.
APIs & Webhooks
The glue: event-driven integration between your existing tools without brittle scraping.
Process
Eight steps.
No surprises.
Step 1
Discovery
We map the workflow, data sources, volumes and success criteria — and confirm automation is actually worth it.
Step 2
Architecture
Written technical design: models, data flow, human review gates, security boundaries and cost estimates.
Step 3
Prototype
A working proof on your real data within weeks — validating quality before full investment.
Step 4
Development
Production build with weekly written updates, staged previews and review cycles.
Step 5
Testing
Evaluation sets, edge-case testing and guardrail verification against your quality bar.
Step 6
Deployment
Containerized rollout to your infrastructure or ours, with documented runbooks.
Step 7
Monitoring
Logging, cost tracking and quality dashboards — you see what the system does and spends.
Step 8
Improvement
Scheduled reviews to tune prompts, expand coverage and adapt to model updates.
Deliverables
What you receive.
Every AI & automation engagement is delivered as a complete, documented system — owned by you, not locked to us.
+
Source code
Full ownership transfers to you on final payment.
+
System documentation
Architecture notes, runbooks and admin guides.
+
API documentation
Every endpoint and webhook documented for your team.
+
Training
Hands-on sessions so your team operates the system confidently.
+
Deployment
Live rollout on your infrastructure, with CI/CD configured.
+
Monitoring setup
Dashboards for usage, cost and output quality.
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Maintenance plan
A written support agreement with response-time commitments.
Why choose EKSNEKS
Built to run for years, not demos.
Technical expertise
AI systems built by engineers who also run the backend, data and infrastructure around them.
Security
Data boundaries, access control and secrets handling designed in — including fully local options.
Scalability
Queue-based architectures that handle 10× volume without a rebuild.
Maintainability
Documented, testable systems your team — or any team — can take over.
Performance
Latency and cost budgets set per workflow and measured continuously.
Long-term partnership
Model landscapes shift; maintenance agreements keep your systems current.
FAQ
AI & automation, answered.
What can realistically be automated?
Repetitive, rule-adjacent work with digital inputs: document intake, support triage, data entry between tools, reporting, drafting. During discovery we score candidate workflows by volume, error cost and complexity — and tell you honestly which are not worth automating.
Will AI replace our staff?
Our systems remove tasks, not roles. In practice teams redirect hours from copy-paste work to judgment work. Where errors are costly, we keep a human approval step by design.
Is our data safe with AI systems?
Data boundaries are part of the architecture: minimal data sent to model providers, EU processing or fully local models via Ollama where required, and written data-handling terms in the agreement.
Can automation run on our own servers?
Yes. Everything we build is containerized and can run on your infrastructure. Self-hosted n8n and local models mean the full stack can stay inside your network.
How do you prevent wrong or invented answers?
Grounding on your verified content, retrieval with source citations, output validation, evaluation test sets, and human review gates for anything customer-facing or high-stakes.
How long does a typical project take?
A focused automation ships in 3–6 weeks; a prototype on your real data usually exists within the first two. Larger AI applications run 2–4 months with milestone deliveries.
What does an AI & automation project cost?
Indicatively from €5,000 for a scoped automation system. Every project gets a fixed written quote after discovery — including estimated ongoing model and hosting costs, so there are no surprise bills.
What are the running costs after launch?
Model usage, hosting and maintenance. We size these during architecture and include a monthly estimate in the proposal. Most workflow automations run for tens of euros per month, not thousands.
Which AI models do you work with?
Claude, OpenAI and Gemini models, plus local open-weight models via Ollama. We choose per task based on quality, cost and data constraints — and can switch providers later because we build behind an abstraction layer.
Do we need clean data to start?
No. Messy, scattered data is normal — part of most projects is building the intake and cleaning pipeline. What matters is that the data exists somewhere digital.
Can you integrate with our existing tools?
Yes — CRMs, help desks, ERPs, spreadsheets, mailboxes and custom internal systems, via official APIs and webhooks. Integration inventory is part of discovery.
Who owns the system afterwards?
You do. Source code, workflows, prompts and documentation transfer on final payment. Nothing is locked to our accounts or infrastructure.
Related services
Often paired with.
Ready to remove the busy work?
Start with a free discovery call. You'll get a written technical proposal with a fixed quote — before any commitment.