XLS rows → discrepancies for review
From emails and documents to completed work. Automatically.
We build AI agents that handle tasks across your CRM, ERP, email and business tools, while your team stays in control.
Built for your business. Deployed in your infrastructure.
Your systems. An agent that connects the work.
See how information from your systems becomes a reply, a finding or a follow-up task. Then open the workspace to try it yourself.
Product document → fields for review
Role + start date → onboarding steps
Email + CRM → reply with context
Invoice + order → evidence to review
Customer request → task and next step
Image + knowledge base → suggested answer
Role + start date → onboarding steps
CRM + recent emails → meeting context
Product document → fields for review
XLS rows → discrepancies for review
Your existing tools. Connected by agents.
Keep your CRM, ERP, email and website. Agents automate the work between them.
An invoice arrives. Let the finance agent check it against the order.
- Email received
- PDF identified
- Invoice extracted
- Order checked
- Review ready
Could this help your team? We adapt the process to your systems and rules.
Discuss a similar workflowHow many hours go into processing your documents?
Example monthly workload: documents × handling time. Compare these examples with the work your team handles today.
Invoice processing
Open PDF → copy details → match order → flag differences
Invoice extracted and checked against the order.
Your team reviews exceptions and approves.Supplier documents
Read PDF → find product codes → copy specifications into ERP
Product details extracted and structured for your catalogue or ERP.
Your team checks missing details and approves updates.Shipment updates
Check dispatch note → match order → update status → notify customer
Dispatch documents matched, status updates and customer messages prepared.
Your team handles exceptions and controls what is sent.Let AI handle the reading, matching and data entry. Your team focuses on exceptions and decisions.
Built for real business processes.
Different suppliers. Different document formats. One automated process.
Hospitals receive safety data sheets for the chemical products they use. Each supplier has its own document layout, and the files arrive in different languages.
We built ProductRoom to automate this process. AI reads the documents, extracts the safety information and organises it into a consistent, searchable structure. Hospital staff review exceptions instead of processing every file themselves.
“The solution is very well designed and helpful. It takes a tremendous amount of work off our hands, and we can once again focus on other safety-related topics.”
Christian Oertig · Safety Specialist, SIBE
Lucerne Cantonal HospitalExplore the case
The challenge
Previously, a staff member had to open each file, find the relevant safety rules and enter that information manually. The same work had to be repeated across suppliers and document versions.
A service team supports ongoing SDS management. These figures describe hospital staff time, not total service-team effort.
Supplier documents → AI extraction → structured safety information → human review
Discuss a similar processFrom checking documents one by one to reviewing one assessment report.
RMO Agency helps contractors in California with licensing. Before accepting an applicant, its team needs to review their business, finances and background.
We built a workflow that reads these documents, extracts the relevant facts, checks financial inconsistencies and gathers reputation evidence with links to its sources. It brings the findings into one assessment report, with explanations behind the checks and risk score.
Explore the case
The challenge
Previously, a reviewer had to work through application documents, bank statements and background reports, check for inconsistencies and research the business’s reputation. The findings then had to be brought together for a decision.
What we built
We built an AI-powered workflow that extracts application and financial data, checks inconsistencies, researches business reputation and prepares a structured assessment report.
For the manual assessment process, as described by RMO Agency.
Documents → AI extraction → financial & reputation checks → report → human decision
Discuss a similar process
Read the trial protocol once. Reuse its requirements for the next task.
Before a clinical trial can start at a clinic, the study team needs to check whether that clinic has suitable patients, equipment and the ability to carry out the required procedures.
The Awairis pilot brings these steps into one workflow. AI extracts requirements from the protocol, flags missing or conflicting information for review and uses the reviewed information to prepare a study-specific questionnaire.
Explore the case
The challenge
The requirements are described in a detailed trial protocol. Preparing a site-assessment questionnaire means finding those requirements in the document and turning them into specific questions for each clinic to answer.
What we built
The team can check and correct the extracted facts. Each questionnaire stays linked to the protocol version it was generated from, so reviewers can trace where its requirements came from.
Trial protocol → extracted requirements → expert review → site-assessment questionnaire
Discuss a similar processAn AI answer is a starting point. Completed work is the goal.
Connect the documents, decisions and actions — without your team moving every step manually.
Give each agent a role, permissions and a clear set of tasks.
An assistant can read relevant documents, prepare replies, check information and carry out permitted actions across your systems. You decide what it can see, what it can do independently and where a person must approve.
Explore roles and tasks
- A separate scope for each role or process
- Access only to relevant systems and information
- Human approval at agreed decision points
- Visibility into actions, usage and costs
Start with the work that takes the most time from your team. We build the automation around it.
Explore example workflowsYour existing software is the starting point.
Connect your CRM, ERP, email and custom software so information moves with the work, instead of being copied by hand.
Familiar examples. Not a closed list.
CRM & customer data
ERP & finance
Email & collaboration
Connect the tools you already rely on through their APIs — including your own software.
From incoming information to completed work, across the systems your team uses.
Plus your websites, documents and custom APIs.
Not every process needs AI. If your existing software or a simpler automation solves the problem, that belongs in the discussion.
Clear boundaries for real business processes.
An assistant gets a defined task and limited access, not the keys to your entire company. We agree the controls before enabling actions.
- Access limited to the task
- Your team approves sensitive actions
- Actions and exceptions stay visible
Explore technical controls
How a request reaches your systems
- Your requestA person or an agreed trigger
- Agent & permission checkOnly permitted data and tools
- Prepare the actionCheck sources and business rules
- Approval when requiredA person reviews sensitive actions
- Execute & recordAllowed API action and visible result
Rights by role
Grant only the system access and actions needed for the task. A sales assistant does not automatically get access to payroll.
Separate data boundaries
Define which sources and workspaces each role may use. Choose isolation controls appropriate to the sensitivity of your information.
Secrets outside the agent
API keys stay outside prompts and chats, in protected secret storage. OneCLI or an agreed access mechanism controls integration access.
Human approval
Agree which emails, record changes and financial or HR actions need review. Approval applies to the prepared action, not a blanket permission.
Audit and visibility
Make actions, results, usage and costs visible to authorised people. Agree what is logged and how long it is retained.
Failures stay visible
Plan controlled retries and manual recovery. Test partial failures and agree who handles incidents and API changes before launch.
Deploy in Azure, AWS, Google Cloud or another agreed environment. Define what can reach AI providers, where processing happens and how retention works. Hosting in your cloud does not automatically keep all processing there.
One place to see progress and make decisions.
When existing interfaces are not enough, we build a dashboard around your operations: status, results, exceptions, approvals and actions across connected systems.
Source evidence and approvals, alongside the work.
Work in familiar tools, with a custom dashboard where your team needs a clearer overview.
Built by software engineers, not AI hobbyists.
Our engineers turn document, image and voice capabilities into working business processes — connected to your systems and built around your team.

Implementation from €10,000.
From analysis to a trained team: we build and deploy automation for your business. Your proposal defines the scope and price. Hosting, API/AI usage and support are separate operating costs.
- Analyse your business processes
We map your manual work, systems and constraints, then agree the workflow, permissions and acceptance criteria with your team.
- Build automation for your business
We build and test automation tailored to the agreed process, your systems and your business rules.
- Deploy in your infrastructure
We deploy the solution in your infrastructure, with agreed access, configuration and operational responsibilities.
- Train your team
We train your team to use the solution, review its work and handle exceptions, with a practical handover.
What could less repetitive work be worth?
Use the people involved in one process, not your entire headcount. Change the assumptions to match your business.
Enter valid values within the indicated limits.
Calculation: people × hours per week × assumed reduction × 52 ÷ 12. Value = released hours × hourly cost. The 20% starting value is an editable example, not a forecast.
Released capacity is not automatically a cash saving. This estimate excludes implementation, hosting, API/AI and support costs. Validate the assumptions in a pilot.
Discuss this processBefore you connect your systems.
How is this different from a standalone AI chat?
The focus is a defined workflow across your systems: relevant context, permitted actions, review points and traceable results. A chat can be one interface, not the whole solution.
Can the agent send emails or change records?
Where the API and your permissions allow it. We agree which actions may run automatically and which require human approval before implementation.
What happens to our data and API keys?
We agree the data flow, hosting, model providers and retention for your solution. Integration secrets stay outside prompts in protected storage; access is limited to the agreed scope.
Do we need to replace our CRM or ERP?
No replacement is required by this approach. We assess your existing APIs first, including custom systems, and identify any constraints before committing to scope.
What happens after we contact you?
Start with one manual process and the systems involved. Together we assess feasibility, agree a measurable pilot scope and provide a proposal. No fixed delivery date or saving is promised before that assessment.
Which workflow is slowing your team down?
Tell us where your team loses time. Together, we identify a useful first process to automate. Implementation starts from €10,000.
Your Dutch point of contact: Sander connects your business process and priorities with the SapientPro engineering team.
