Your Outcome-First Intelligence Layer for Manufacturing.
Recapi builds manufacturing-specific AI intelligence around your processes, operational rules and business goals. It understands the depth of your manufacturing workflows and creates personalized, outcome-driven systems designed for the way your business actually operates.
- Outcome-First Intelligence
- Pre-Trained Manufacturing Intelligence
- Simulation-Led Data Gap Resolution
- On-Premise Deployment
Manufacturing Intelligence Layer
Supplier Delay
Identify the problem
Supplier delivery delayed. Material required for upcoming production orders.
Assess the impact
Identify affected production orders, check available inventory, identify material gaps and evaluate alternative production schedules.
Take the right action
Update affected production schedules, reallocate available inventory and initiate approved procurement or supplier follow-ups.
Continuously Measures, Learns and Improves
- Measures the task as it happens
- Learns from the outcome
- Improves future decisions and execution
Operational outcome
Know which orders are at risk and what needs to change before production is disrupted.
Manufacturing Has Data. What It Needs Is Intelligence.
Manufacturers have invested in ERP, MES, automation and analytics. But critical knowledge remains fragmented, operational decisions still depend on experienced people, and existing systems often struggle to coordinate actions across departments.
01
Disconnected Operational Data
Production, inventory, procurement and quality data live across different systems, making it difficult to understand the complete operational picture.
02
Missing Domain Knowledge
Critical manufacturing knowledge sits with plant managers, engineers and experienced employees. It is rarely captured in a form AI systems can reliably use.
03
Limited Outcome-Driven Execution
Traditional systems report problems and automate predefined tasks. They struggle to adapt when conditions change or when achieving an outcome requires coordination across multiple functions.
One intelligence layer. Across your entire manufacturing operation.
Recapi turns fragmented operational data, undocumented expertise and existing business workflows into domain-specific AI systems.
Instead of creating isolated AI tools for individual tasks, build intelligent systems that understand your operational goals and coordinate the work required to achieve them.
Production Planning & Scheduling
Move from reactive production planning to intelligent production coordination.
- Generate production schedules using orders, machine capacity, material availability and delivery commitments.
- Recalculate schedules when machines fail, materials are delayed or priorities change.
- Identify bottlenecks and production conflicts before they affect delivery.
- Coordinate production capacity across multiple plants and manufacturing lines.
- Recommend the best production sequence based on operational constraints.
Supply Chain & Procurement Intelligence
Know what to procure, when to procure it and what could disrupt your supply chain.
- Identify material shortages before they interrupt production.
- Monitor supplier performance, delivery reliability and procurement risks.
- Recommend alternative suppliers based on availability, cost and lead time.
- Prioritize purchase requirements according to production demand.
- Coordinate procurement decisions across multiple plants and suppliers.
- Identify dependencies that could affect production commitments.
Inventory & Warehouse Intelligence
Keep inventory aligned with actual production requirements.
- Monitor inventory against production plans and material requirements.
- Identify excess stock, slow-moving inventory and potential shortages.
- Recommend stock transfers between warehouses and facilities.
- Optimize replenishment decisions using demand and lead-time information.
- Identify inventory discrepancies across connected systems.
- Coordinate material availability with upcoming production schedules.
Quality Management & Defect Intelligence
Identify quality problems, understand their causes and prevent repeated failures.
- Analyze inspection results, quality reports and historical defects.
- Identify recurring defect patterns across production batches.
- Connect quality failures with machine settings, materials, suppliers and operating conditions.
- Support root-cause investigations.
- Recommend corrective and preventive actions.
- Monitor whether corrective actions are improving quality outcomes.
More Than Automation. Intelligence That Learns and Works Towards Outcomes.
Recapi provides the infrastructure to build specialized, outcome-driven AI systems for complex manufacturing environments.
01
Goal Intelligence
Define the operational outcome. Recapi builds AI systems around what needs to be achieved, rather than limiting them to predefined tasks.
02
Simulation-Led Knowledge Acquisition
Identify missing domain knowledge and data gaps. Use conversational simulations to capture critical knowledge from manufacturing experts and experienced employees.
03
Real-Time QA & Self-Learning
Benchmark AI performance against defined goals and rules. Use execution feedback and changing operational context to continuously improve system performance.
04
Enterprise-Controlled AI
Choose suitable models, connect enterprise data and control how AI systems access information and execute actions. Support private and on-premise deployment requirements.
From fragmented manufacturing knowledge to intelligent operations.
- Step 1
Connect your manufacturing ecosystem
Connect ERP, MES, QMS, CMMS, WMS, databases, documents and other relevant business systems.
- Step 2
Define your business outcomes
Tell Recapi what you want to achieve: reduce production delays, improve inventory availability, optimize scheduling or improve quality management.
- Step 3
Discover missing knowledge
The Simulation Engine identifies missing information and conducts targeted conversations with your employees and subject matter experts.
- Step 4
Build domain-specific intelligence
Combine operational data, captured knowledge, industry-specific datasets and selected AI models to build intelligence aligned with your processes.
- Step 5
Execute business workflows
Connect the required tools and systems. Let AI coordinate the tasks and workflows required to achieve the defined outcome.
- Step 6
Benchmark and continuously improve
Evaluate accuracy, identify performance gaps and improve through feedback, additional knowledge and controlled learning.
- Step 7
Deploy and scale
Deploy your AI systems within your preferred infrastructure. Reuse successful workflows and templates across facilities and business units.
See what happens when your AI understands the entire operation.
Scenario 1 / 4
A critical supplier misses a delivery.
Desired outcome
Minimize production disruption and protect delivery commitments.
Instead of simply notifying the procurement team, your AI system:
- 1Identifies which production orders depend on the missing material.
- 2Checks available inventory across warehouses and facilities.
- 3Evaluates alternative suppliers and procurement timelines.
- 4Identifies production schedules at risk.
- 5Recommends revised schedules and material allocation.
- 6Escalates decisions requiring human approval.
Don't replace your manufacturing software. Make it work intelligently together.
Recapi is designed to work with the systems your business already depends on.
Connect. Understand. Coordinate. Execute.
Recapi provides an intelligence and execution layer across your existing technology ecosystem.
Enterprise data sources
- ERP systems
- MES platforms
- QMS and quality databases
- CMMS and maintenance systems
- WMS and inventory platforms
- CRM and order management systems
- SQL databases and internal repositories
- Documents, SOPs and technical manuals
- IoT and machine data sources, where available
Your manufacturing intelligence should remain under your control.
Manufacturing data can include proprietary formulations, machine parameters, production methods, supplier agreements, customer specifications and confidential operational knowledge.
Your AI infrastructure should respect that ownership.
Recapi supports:
- Private & On-Premise Deployment
- Model & Data Ownership
- Role-Based Access & Permissions
- Controlled AI Actions & Integrations
- AI Security & Protection
- Human Oversight & Approval
Build AI around your business without surrendering control of your business knowledge.
Manufacturing expertise deserves AI that understands manufacturing.
| Traditional AI tools | Recapi |
|---|---|
| Depend on available training data | Actively identifies missing knowledge |
| General-purpose intelligence | Domain-specific intelligence |
| Static configurations | Continuous learning and improvement |
| Task-oriented automation | Outcome-driven execution |
| Separate tools and workflows | Reusable infrastructure across operations |
| Limited visibility into accuracy | Real-time QA and benchmarking |
| Vendor-dependent deployment options | On-premise and customer-controlled deployment options |
Frequently Asked Questions
Can Recapi work with our existing ERP and MES systems?
Recapi is designed to connect with enterprise systems and operational data sources through supported integrations and APIs. The exact integration scope depends on your systems and deployment requirements.
Does Recapi replace our existing manufacturing software?
No. Recapi is designed as an intelligence layer that works with your existing operational systems.
Can we deploy Recapi on-premise?
Recapi supports private and on-premise deployment requirements, depending on the agreed architecture and implementation scope.
How does Recapi understand our manufacturing processes?
Recapi uses your enterprise data, documents and domain knowledge. Its Simulation Engine can identify missing knowledge and capture it through structured conversations with subject-matter experts.
Can we control what the AI systems are allowed to do?
Yes. Access permissions, API actions and approval requirements can be configured to match your operational and security policies.
How does Recapi measure AI performance?
Through real-time QA and benchmarking against defined goals, rules and performance criteria.
Bring Intelligence Into Your Manufacturing Operations.
Build AI systems that understand your domain, work towards business outcomes and improve with every operational cycle.