Automating the old process
Putting a bot or a language model on top of a broken process makes the broken process faster. The duplicate steps, the waiting and the rework stay.
AI & Business Process Automation Assessment
We don't start with AI. We start with the work.
Don't automate the old process. Redesign the way the work gets done. A fixed-price assessment that maps how work really flows through your business, removes what should not be there, and applies automation and AI only where they create measurable value.
Sound familiar?
Where the work gets stuck.
- Critical processes run on spreadsheets and email threads that only a few people can follow.
- Teams re-key the same data into several systems, and errors surface downstream.
- Approvals wait for days in inboxes, and nobody can see where a request stands.
- Your SaaS applications do not talk to each other, so people do the integration by hand.
- Skilled staff spend hours every week on repetitive administrative tasks.
- Answers depend on knowing who to ask, or on documents nobody can find.
- Growth means hiring more people to do the same manual work.
- You have tried AI tools, but the way the work actually gets done has not changed.
Why the usual approach falls short
Why most automation projects disappoint.
Starting with the tool
Choosing a platform before understanding the work leads to proofs of concept that impress in a demo and never reach production.
AI where a rule would do
Many steps are better served by a business rule, an API call or a simple workflow: cheaper to run, faster, and easier to audit.
Governance as an afterthought
Without clear controls on data, privacy, auditability and human approval, pilots stall at the risk and compliance review, or create exposure nobody signed off on.
The Copernicus approach
Redesign the work first. Then choose the technology.
We map how the work really happens, remove what should not exist, and only then decide, step by step, what each part of the process needs. Often that is a rule or an integration. Sometimes it is an AI agent. Sometimes it should stay with a person.
- Deterministic business rulesWhere the logic is known and must be exact.
- Workflow automationRouting, approvals, notifications and hand-offs.
- APIs and system integrationSo data is entered once and flows everywhere it is needed.
- Data pipelinesReliable, timely data for reporting and decisions.
- AI agents and LLM-based reasoningFor unstructured inputs, classification, drafting and multi-step tasks.
- Enterprise knowledge retrieval (RAG)Answers grounded in your own documents and records.
- Human-in-the-loop approvalPeople confirm what matters before it takes effect.
- Human judgmentWhere risk, relationships or accountability require it.
- Understand the workWalkthroughs with the people who do the work, and the systems, documents and data it touches.
- Map and measureVolumes, cycle times, hand-offs, error rates, and where capacity is lost.
- RedesignSimplify, remove duplicate steps and rethink approvals before anything is automated.
- Match each step to the right approachRules, integration, workflow, AI or a person, chosen on value, risk and complexity.
- Prioritize and planA 90-day roadmap and one well-defined pilot that proves value quickly.
What we assess
The work, and what it would take to change it.
The work and its economics
- Process mapping, as the work really happens.
- Bottleneck identification.
- Automation opportunities.
- AI agent opportunities.
- Expected capacity improvement.
- ROI and implementation complexity.
The foundations and the controls
- System and integration requirements.
- Data and knowledge readiness.
- Security, privacy, auditability and governance.
- Human control and escalation points.
Deliverables
What you receive.
A plan your operations, finance and technology leaders can agree on, with the numbers to support it.
Process Automation Opportunity Map
Your key processes, where time and money are lost, and which steps should be redesigned, automated, supported by AI or left with people, ranked by value and effort.
Prioritized use cases
The opportunities worth pursuing first, each with its expected benefit, dependencies and risks.
Target automation architecture
How workflows, integrations, data and AI components fit with the systems you already run.
Recommended technology approach
The tools and frameworks that suit your processes, architecture and governance requirements, and why.
90-day automation roadmap
What to do first, who is involved, and what success looks like at each step.
ROI and capacity model
Hours released, cycle-time gains and running costs, set against the investment required.
One defined initial pilot
Scope, success criteria, controls and budget for a first pilot you can start immediately.
Business outcomes
What the business gets out of it.
- Capacity to grow without adding headcount for repetitive work.
- Shorter cycle times for approvals, onboarding, quoting and reporting, measured before and after.
- Fewer errors and less rework, with data entered once and checked at the source.
- Controlled risk: automated steps are traceable, and people approve where it matters.
- Better use of skilled people, moving time from administration to customers and judgment.
- A credible investment case, with ROI and complexity known before budget is committed.
Why Copernicus
Enterprise architects first, not an AI agency.
Process and architecture, not just prompts
Automation that lasts depends on integration, data quality and reliable operations. We have spent thirty years building and running mission-critical enterprise platforms.
Technology-independent
We are not tied to a single AI vendor or automation platform. The framework is chosen for your process, your existing architecture, your governance requirements and the outcome you need.
Governance built in
Security, privacy, auditability and human oversight are designed in from the first workshop, with the EU GDPR discipline we apply to all our work.
We advise, then we build
The people who design the roadmap can deliver the pilot and scale it, with a senior near-shore engineering team working in your hours.
Modern AI and agentic architectures, chosen on merit
Depending on the process, we work with technologies such as:
- OpenAI
- Anthropic
- LangGraph
- Microsoft Agent Framework
- Google ADK
- LlamaIndex
- MCP-based integrations
- n8n and workflow orchestration
- Custom Python and API integrations
Engagement model
Fixed scope, fixed price, senior team.
- Investment
- Fixed price, starting at $7,500 for a focused business area. Multi-department or enterprise assessments typically start at $12,500. The price is agreed before we start.
- How it runs
- Working sessions with process owners and the people who do the work, review of the systems and data involved, and a readout with leadership.
- Where we work
- With mid-market and enterprise companies across the United States, including Florida (Miami, Tampa, Orlando), and in Europe. Remote by default, on-site when it helps.
- Afterwards
- You leave with a pilot ready to start. Run it with your own team, or with Copernicus through near-shore delivery.
Bring us one process that costs you too much time.
Start with a 20-Minute Technology Opportunity Review with Renaud Arnoux-Prost. If an assessment makes sense, you will know its scope and price before you commit.