AI automation for the manual work slowing your team down
We automate document handling, email triage, approval routing, data extraction, and cross-system workflows, with human review for uncertain cases and audit logs for production use.
Tell us the manual process. We’ll tell you whether AI, a simpler script, or no-code automation is the right fix.
Manual workflows we can automate
Knowledge-base automation
Employees ask questions across SOPs, wikis, policies, and project documentation. The system retrieves answers from approved sources, respects access permissions, and routes uncertain cases to human review instead of guessing.
- Indexes your docs, wikis, SOPs and knowledge bases - Notion, Confluence, SharePoint, Google Drive, custom sources
- Cuts manual search time - employees get direct answers in seconds instead of searching dozens of pages or asking colleagues
- Access-controlled by team or role - only shows content the user is allowed to see
- Stays current automatically - re-indexes when source content changes, no manual updates
Email & request routing
Incoming emails classified by intent, priority, and customer type. Tickets are created, CRM records are updated, and the right team is notified. When the system is not confident, it queues for human review instead of guessing. Works with Gmail, Outlook, and custom inboxes.
- Classifies by intent, priority, and customer type - support/sales/billing/complaint handled differently from the first line
- Creates tickets and updates CRM automatically - HubSpot, Salesforce, Zendesk, Intercom, or your custom system
- Queues uncertain cases for human review - system admits uncertainty instead of guessing and getting it wrong
- Works with Gmail, Outlook, and custom inboxes - no change to how senders send, no inbox restructuring needed
Document processing
Invoices, contracts, applications, PDFs, scans. Fields extracted, documents classified, exceptions flagged, data pushed to your ERP or CRM. Accuracy is benchmarked on your documents before go-live, with human review for low-confidence cases.
- Invoices, contracts, applications, PDFs, scans - structured and unstructured formats, handwritten fields where legible
- Accuracy benchmarked on your documents before go-live - for consistent document types, 95%+ extraction accuracy is often realistic, confirmed during the proof of concept
- Exceptions flagged for human review - system does not guess when confidence is low, it queues for review
- Data pushed to ERP, CRM, or custom destination - JSON, CSV, direct database insert, or webhook to your system
Approval & exception workflows
Expense approvals, contract sign-offs, compliance checks. Routine cases handled automatically, edge cases escalated to the right person. Every decision is logged with a full audit trail. Works across any industry with defined approval rules.
- Expense approvals, contract sign-offs, compliance checks - any workflow with defined rules can be automated
- Routine cases handled automatically - edge cases escalated to the right person, not everyone on the team
- Full audit trail for every decision - who approved, what the data was, when it happened, all logged
- Works across any industry with defined approval rules - finance, legal, HR, procurement, compliance
Data extraction & enrichment
Pull data from approved websites, PDFs, reports, or raw API responses where automated access is allowed. Transform it into structured tables, trigger alerts, or feed downstream systems. Built for cases where no official API exists or the source data is too inconsistent to handle manually.
- Data extraction from approved sources, APIs, documents, and websites where automated access is allowed - intelligent parsing, not fragile CSS selectors
- Transforms into structured tables or triggers alerts - feeds downstream systems, dashboards, or data warehouses
- Built for cases where no official API exists - with retry logic, change detection, and clear limits around allowed automated access
- Retry and error handling included - failed extractions logged, retried, and flagged rather than silently dropped
Cross-system integrations
When Zapier is not enough. Complex multi-step logic, conditional branching, retry handling and custom error recovery. We connect your internal tools, legacy APIs and SaaS platforms into one coherent automated flow.
- Multi-step logic with conditional branching - if this, then that, else escalate. More than Zapier can handle
- Retry handling and custom error recovery - failed steps are logged, retried, and routed to human if needed
- Connects legacy APIs, SaaS tools, and internal systems - REST, GraphQL, webhooks, custom connectors
- Production-grade reliability - monitoring, alerting, and full trace logs for every automated action
When AI automation is worth building
Not every process needs AI. We look for repetitive work with clear inputs, repeatable decisions, and enough volume to justify the build.
Good fit
High-volume document handling, repeated email classification, approval routing, knowledge lookup, data extraction, and workflows where human review can handle the exceptions.
Not a good fit
Processes with unclear rules, very low volume, poor data access, or cases where a simple rule-based script would solve the problem faster and cheaper.
Human in the loop
For sensitive decisions the system suggests, routes, extracts, or summarizes. A person reviews low-confidence or high-risk cases before any action is taken.
Measured before rollout
We test accuracy, time saved, error rates, and edge cases during the proof of concept before recommending a production build. You decide based on real numbers.
Automation stack chosen for the workflow
We use managed AI APIs, document extraction tools, workflow engines, and custom backend code depending on reliability, data sensitivity, and integration needs.
AI models and APIs
OpenAI, Anthropic Claude, Mistral, Llama, and other open-source models selected by use case, cost, latency, and data requirements.
Documents and extraction
OCR, PDF parsing, AWS Textract, Azure AI Document Intelligence, custom parsers, extraction validation, and human-review queues for low-confidence cases.
RAG and knowledge retrieval
LangChain, LlamaIndex, embeddings, semantic search, access-controlled retrieval, and vector databases such as pgvector, Qdrant, Weaviate, or Pinecone.
Workflow orchestration
n8n, Make, webhooks, queues, scheduled jobs, approval flows, retries, error handling, and custom Python or Node.js services when no-code tools are not enough.
Product and system integration
REST and GraphQL APIs, CRM, ERP, email, helpdesk, internal tools, authentication, role-based access, and audit logs.
Deployment and monitoring
FastAPI, Docker, cloud or private-cloud deployment, logging, alerting, traceable workflow runs, and cost monitoring for production automation.
From manual process to monitored automation
-
01
Map the manual workflow
We review inputs, outputs, tools, decision rules, exceptions, volume, and business value. If a simpler script or rule-based automation is enough, we say so early.
-
02
Build a focused proof of concept
We test the workflow on a realistic sample of your data in 2–4 weeks. You see accuracy, edge cases, time saved, and failure points before a full build.
-
03
Add controls for production
We add access control, human-review queues, approval logic, retries, error handling, audit logs, and monitoring.
-
04
Connect your systems
We integrate with your CRM, ERP, inbox, helpdesk, database, or internal tools, then test edge cases in staging before go-live.
-
05
Launch, train, and improve
Your team gets documentation and handoff. After launch, we monitor failures, costs, and user feedback, then adjust the workflow logic where needed.
Common questions
How long does a typical automation project take?
A focused proof of concept typically takes 2–4 weeks. A first production automation with integrations, human-review logic, and audit logging usually takes 6–12 weeks. We always start with a scoped proof of concept so you can evaluate results before committing to the full build.
Do you work with sensitive or proprietary data?
Yes. We sign NDAs from day one, build with GDPR-aware data handling, and can deploy on-premise or in your private cloud if the data cannot leave your infrastructure.
Can you integrate with our existing tools?
We work with most major APIs, CRMs (HubSpot, Salesforce), project tools (Jira, Notion), communication (Slack, email), ERPs, and custom internal systems.
What if the AI makes mistakes?
Every production pipeline we build includes confidence thresholds and human-review queues for low-confidence cases. The system flags uncertainty instead of guessing.
What does it cost?
A short automation scope check can start from €1,000–5,000. A focused proof of concept usually ranges from €3,000–15,000. A first production automation with integrations, access control, logging, and human-review logic usually starts from €7,000–30,000. More complex workflows are estimated after we review your systems, data, edge cases, and security needs.
Do we need to provide training data?
Not always. Many LLM-based automations work with prompting and your existing documents. Custom fine-tuning is only needed for specialized domains or performance at scale.
Do we always need AI for automation?
No. Some workflows are better solved with a rule-based script, API integration, or no-code automation. We use AI when the process involves unstructured text, documents, variable inputs, classification, summarization, or decisions where simple rules are too brittle. If a simpler approach is enough, we say so early.
What happens after the automation goes live?
We monitor failures, edge cases, cost, and user feedback after launch. When APIs change, document formats shift, or business rules evolve, we adjust the workflow logic, prompts, extraction rules, or integrations.
You might also need
AI development
Build AI features into your product: LLM integration, RAG systems, AI agents, and custom AI-powered functionality.
AI document processing
Specialized extraction pipelines for invoices, contracts, forms, and scanned documents at scale.
AI chatbots
User-facing assistants trained on your content. Answer questions, qualify leads, support customers.
Web development
Need a dashboard to monitor your automation? We build the interface too.
What would you automate first?
Tell us what your team does manually every day. We’ll assess what’s worth automating and what isn’t, and get back within 48 hours with a realistic opinion, not a pitch.
Describe what you want to automate →