From project engagement to the 12+ month journey.
For implementing your AI and automation solutions we offer flexible collaboration models – from classic project engagements through Managed Composable AI Solutions to long-term support as part of a 12+-month journey.
Project engagement
We deliver an automation or AI project based on a prior effort estimate and quote, clearly scoped, with fixed scope and sign-off.
Managed Composable AI Solution
We operate one of our ready-made Business Solutions for you, for example accounts-payable processing. After a one-off integration fee, we deliver and license the service continuously under an ARR model.
12+ month journey
Fixed capacity instead of a single order: several use cases run in parallel over 12 months, guided by the AI Transformation Lead, our approach for sustainable scale.
From quote to sign-off.
Requirements & quote
We capture the process and requirements together, estimate the effort and fix scope, timeline and price in a quote, including sign-off criteria.
Development in sprints
Our engineer team delivers the defined scope in short sprints. Weekly demos show progress, scope changes are handled transparently as change requests.
Testing, handover & hypercare
We go live after joint user acceptance testing. A hypercare phase secures stable operation; afterwards we hand over to your team or move seamlessly into the capacity model.
We operate the use case for you.
Connection & integration fee
A one-time fee for connecting to your systems. ERP, mail, document storage, and configuring the use case, for example accounts-payable processing.
Ongoing operation under ARR
We operate, monitor and maintain the use case continuously, including monitoring, defined SLAs and support. Billed monthly as a predictable ARR license, not per project.
Continuous optimisation
New document types, edge cases and rule changes are folded in continuously. A biannual review tracks performance and savings against the agreed KPIs.
From first conversation to outcome.
Discovery & potential analysis
The AI transformation lead gets to know your company. Together we identify use cases with real business value, prioritised by ROI and feasibility. The result is a clear roadmap with measurable goals.
Parallel delivery
Multiple processes run in parallel: our engineer team builds and operates, the AI transformation lead prioritises and coordinates. Use cases go live wave after wave, you see continuous progress, not presentations.
Savings measurement & next wave
At year-end we add up the outcome across all use cases: realised savings and ROI, measured against the baseline from the start. From that we build the roadmap for the next year.
More automation per year.
Project by project means contract overhead before every step. With fixed capacity, several use cases run in parallel, more delivered, higher savings.
Each automation commissioned separately: scoping, quote, sign-off, then the next one. Much runs sequentially.
Fixed capacity, applied continuously: several use cases run in parallel, without contract overhead between each step.
More automations delivered per year means more hours and costs saved, the effect compounds across the year instead of starting over with the next project. Illustrative; we pin the concrete figures together in the outcome charter.
Capacity that grows with you.
Fixed monthly engineering capacity, from the first use case to enterprise rollout. ARR-based, annually predictable.
Start
For SMEs that want to bring a first use case into production, with clear structure and a manageable budget.
Build Recommended
Several use cases in parallel workstreams. Ideal for mid-market companies with clear automation potential.
Scale
Enterprise environments with multiple departments, complex ERP integrations and ambitious outcome goals.
Outcome charter, transparency from the start
Every engagement starts with a jointly signed outcome charter: 3–5 measurable KPIs, baseline measurement at the start, defined measurement methods. No black box, full accountability on both sides.
And this is how a project runs.
From the first description to live operation takes weeks, not months. The process owner describes the workflow, AI consultant and AI engineers build it. Depending on the case, AI, a validation app and RPA come into play, individually or combined. AI engineers connect the required ERP and line-of-business systems and make the relevant company knowledge available.
We write the PDD
(Process Definition Document)
Why Automatify
Technology scouting
We continuously review new LLM models as well as RAG and automation approaches and evaluate how they can make processes even more efficient.
Interdisciplinary teams
AI, data, RPA and software engineers work together on end-to-end workflows, no silo handoff between the different disciplines.
Partnerships
We work closely with Microsoft, UiPath, Anthropic and Snowflake, and take part early in their early-adopter programmes.
Smart people
Our consultants, solution architects and software developers all hold a university degree in computer science and strong social skills, essential for successful online collaboration. The average age of our team is 27 years.
Ready for the first step?
30 minutes. No sales pitch, a real conversation about your processes and where AI creates value.