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Hosted / Managed Automation
Workflows run on VasthavM-managed infrastructure with monitoring, alerts, support, and monthly improvement capacity. Your team gets the outputs without carrying the ops burden.
Services
AI & automation services for growing businesses
Fixed-price SMB wedges, audits, sprints, agent pilots, and managed automation — built on n8n, Make.com, Python, OpenAI, and Anthropic. Start with one named outcome, then expand into a managed or owned operating model.
Productized offers
Start with the audit, then build what pays back
A clear path from workflow diagnosis to practical automation sprints, scoped AI agents, retainers, and documentation-heavy handover.
Delivery model
Hosted by default, owned when you need it
Most SMBs should not operate n8n or automation infrastructure themselves. VasthavM can run it for you, with a premium handover option when internal control is the priority.
Premium
Owned / Handover Build
Workflows deploy into your accounts or infrastructure with documentation, credentials notes, and owner training. Higher upfront cost, lower dependency on ongoing management.
No vendor lock-in means the operating model is explicit: managed hosting for speed and reliability, owned handover when your team is ready to run it.
SMB proof slot
First Swedish SMB result slot
Reserved for the first named Swedish SMB result from Lead-to-CRM Capture or Monday Brief: buyer profile, workflow shipped, measurable before/after, and what changed operationally.
Common scenarios
What I Solve for businesses
Recurring situations I see in growing companies — pick one to see how I approach it and what changes.
01
Too many apps; nothing talks to each other cleanly
Unify CRM, email, finance, and support into orchestrated flows — not another tool to manage.
Approach
I design orchestration across your stack (CRMs, email, finance, support) with n8n, Make, and Python glue code where needed.
What changes
- One coherent flow instead of swivel-chair work
- Fewer copy-paste errors
- Clear ownership per step
Tools I build with
I'm tool-pragmatic: pick what survives production, not what trends on LinkedIn. I'm equally happy meeting clients on the stack they already run — Microsoft, Google, Azure — as I am running self-hosted infrastructure end-to-end. The current default stack:
01 — Orchestration & automation
Where the workflows actually run
n8n
Managed workflow orchestration by default for SMB automation; owned deployment when internal operation is required.
Make.com
Cloud orchestration when self-hosting isn't a fit. Faster to ship, less control.
Power Automate
Microsoft's enterprise workflow platform — the right call when clients are deep in Microsoft 365, SharePoint, Teams, and Dynamics.
Prefect
Python-native orchestration for data and ML pipelines that need observability and retries.
02 — Data engineering
Pipelines, transforms, source of truth
Python
Custom logic, reliability glue, data transforms — anything an off-the-shelf node can't do cleanly.
dbt
Modular SQL transformations with version control, testing, and documentation built in.
dlt
Lightweight Python ELT — load data from any API into your warehouse with schema evolution.
Postgres / Supabase
Source-of-truth storage, vector search, auth, and edge functions in one place.
03 — AI & agents
The reasoning layer
LangChain / LangGraph
Agent orchestration and tool-use patterns when the workflow needs reasoning, not just routing.
OpenAI
GPT models for breadth and tool use. Always evaluated, never assumed.
Anthropic
Claude for reasoning and long-context work. Default choice for high-stakes outputs.
Google Gemini
Strong on multi-modal reasoning, native tool use, and long context. Routed via Vertex AI for clients on Google Cloud.
Nano Banana Pro
Google's premium image generation model — production-grade visual assets with strong prompt adherence. For marketing automation and content workflows.
04 — Infrastructure & deploy
Where it all runs
Coolify
Self-hosted PaaS for clients who need on-prem or sovereign deployment.
Cloudflare / Cloudflare One
Domain handling, DNS, Zero Trust security, Workers, and edge protection.
Terraform
Infrastructure as code — repeatable, reviewable, version-controlled environments.
Vercel
Hosting for the user-facing layer when speed of iteration matters.
Railway
Backend services and APIs in single-region deploys.
05 — Workspace integration
Working with the tools your team already uses
Microsoft 365 / Azure
Deep integration with Microsoft Graph, Azure OpenAI, SharePoint, and Teams — for clients running on Microsoft.
Google Workspace
Drive, Gmail, Calendar, Docs, and Workspace Add-ons — for teams running on Google.
Common questions
What does an AI automation consultant actually do?
Three things: (1) figures out where AI and automation fit in your operation — and just as importantly, where they don't; (2) builds and ships those systems on stacks like n8n, Make, and Python; (3) hands them over with documentation so your team owns the result, not me.
How much does a typical engagement cost?
An AI readiness assessment runs roughly 1–2 weeks and starts at fixed pricing. Workflow automation projects depend on scope; a single targeted workflow is typically 2–4 weeks. Larger programs combining assessment, build, and handover run 2–4 months. I price most work as fixed-scope or time-and-materials with a budget cap. Retainers are available after a first engagement.
What size of business is this for?
The sweet spot is companies with 5–250 employees that have outgrown spreadsheets and consumer SaaS but aren't running a dedicated automation engineering team yet. If you have one specific workflow that's costing you time and you can name the cost in hours or money, that's a good starting point.
Do you work with companies outside Sweden?
Yes. Most engagements run remotely across the EU, with on-site visits in Gothenburg, Stockholm, and surrounding regions when it adds value. English and Swedish.
What's the difference between automation and AI agents?
Automation is deterministic — given input X, do step Y. Useful for handoffs, notifications, sync. AI agents add reasoning — given a goal and a set of tools, decide what to do next. Useful for triage, research, customer interactions where outcomes vary. Most projects use both: deterministic flows with AI nodes where judgment is needed.
Can you work with our existing tools?
Almost always yes. Standard integrations cover CRM (HubSpot, Salesforce, Pipedrive), helpdesk (Zendesk, Intercom, Freshdesk), comms (Slack, Teams, email), storage (Drive, SharePoint, S3), and most modern SaaS APIs. If a tool has an API, it can be wired in.
What happens after the project ends?
You get documentation, runbooks, and a clear operating model. Managed Automation covers hosting, maintenance, model updates, and small extensions; Owned Handover gives your team the runtime and responsibility.
Not sure which service fits?
Start with an AI readiness assessment. Two weeks, fixed price, ends with a prioritized roadmap and a budget range — no commitment to a build phase.