Berkshire Grey Announces Robots-as-a-Service (RaaS) for Scalable Robotics Solutions

Adopt Berkshire Grey’s RaaS now to scale your fulfilment footprint while controlling capital outlay. Early deployments show throughput gains up to 30% and daily labor reductions in the 20–40% range as teams replace repetitive tasks with predefined, robotic workflows. This approach maximizes asset utilization and accelerates growth by turning capital into a scalable service, not a fixed asset.

With RaaS, используя a predefined set of management dashboards, operators gain an accessible, real-time view of tasks, throughput, and sortation flows. The platform supports seasonal demand by dynamically adjusting the generation of robot assignments and scaling fleets without new hardware, reducing the footprint of peak seasons while preserving service levels.

The system’s sortation capabilities streamline goods movement, guiding robots to daily pick-and-pack tasks, carton sortation, and pallet handling. By collecting data across a generation of operations, managers learn which sequences maximize throughput and reduce error, enabling continuous improvement in a controlled, accessible way.

Companies can expect an enhanced experience for operators as interfaces simplify task scheduling and exception handling. The RaaS model also includes management services, remote monitoring, and ongoing software updates that maximize uptime and support scalable growth across multiple facilities, from urban DCs to regional hubs.

For teams evaluating automation, start with a predefined rollout plan: select a single fulfilment zone, map repetitive tasks, and align metrics to daily throughput, accuracy, and cycle times. Phased expansion can extend the solution to sortation lanes, order consolidation, and seasonal peaks, with predictable costs and a clear footprint of services.

Overview of Berkshire Grey’s RaaS for Scalable Robotics Deployment

Begin with a modular RaaS pilot in a single industrial warehouse to prove ROI and establish a reliable baseline. Deploy onetouchdistribution to streamline inbound processes and set up pick-to-light to boost picking accuracy from day one. This approach provides clear support for developing a scalable workflow that can be replicated across facilities.

The orchestrated automation layer runs on a dynamic grid of slots and devices, delivering reproducible throughput as volumes fluctuate. The latest modules introduced by Berkshire Grey that integrate with your WMS and ERP provide seamless integration and real-time feedback to managers. This visibility helps reduce drops and keep operations accessible to staff at all levels.

Selecting the right starting SKUs and processes matters. Focus on high-frequency, high-value items, then expand to lower-velocity lines. A three-phase rollout–calibrate, validate, and scale–keeps the grid balanced and prevents overcommitment. According to источник, Berkshire Grey’s approach minimizes risk while delivering measurable gains in throughput and accuracy.

Operational benefits include boosted throughput, improved labor utilization, and a smaller automation footprint in warehouses. The system supports developing a reusable automation layer that can be configured for different layouts and product mixes, with drops in order handling errors and faster replenishment cycles. Accessible interfaces and onetouchdistribution workflows allow teams to manage changes without extensive retraining, while a modular design enables rapid expansion to additional facilities.

Next steps involve locking in a three-to-six-week pilot window, mapping KPIs, and planning a multi-warehouse rollout. Ensure ongoing integration with existing systems, provide ongoing training, and schedule quarterly updates to align with the latest industrial automation capabilities. This strategy helps facilities downsize risk while delivering a scalable, distributed automation backbone.

Operational impact on warehouse operations and order fulfillment

Begin with a phased RaaS rollout focused on high-volume lifting and put-away tasks to lift throughput by 20-35% in the first quarter. This approach reduces labor variability and frees your team to handle exception handling and replenishment more effectively. It also accelerates order cycles and improves accuracy across ranges of SKUs.

1. Throughput, cycle times, and accuracy: In representative brownfield sites, an integrated goods-to-robot line reduces walking and item search, delivering 1.5x–2.2x throughput uplift and 15–40% faster average order cycle times. Pick accuracy improves toward 99.5% when robots confirm item location before lift, and the system provides real-time information about remaining workloads for each zone.

2. Labor roles and individual tasks: Human workers shift to supervision, exception handling, and health and safety monitoring. They supervise the line, intervene only on rare outliers, and handle replenishment alongside robot-led tasks. This part reduces fatigue from lifting heavy pallets and allows your operators to adapt to peak workloads more smoothly alongside automated support.

3. Pallet handling and SKU ranges: The combined goods-to-robot and pallet-handling flows support a broader range of SKUs–from slow-moving items to fast movers–covering mexican facilities and multinational ranges. The operator ensures pallets are staged at the designated bay; robots pick and place along the line, reducing cross-docking times.

4. Data integration, information flows, and southbound interfaces: The integrated system provides southbound data to the WMS and ERP, with information available in real time to planners. This enables better load balancing across shifts and allows you to adapt to abrupt changes in demand. It also introduces a feedback loop that informs restock decisions and slotting.

5. Brownfield deployment, mexican facilities, and scalability: RaaS enables scalable deployments by adding or removing robot units to align with workloads. In multi-site networks including mexican warehouses, you can convert brownfield floorspace to goods-to-robot lines without large capex. The platform provides predictable capacity and supports quick ROI when paired with proven software and hardware integration.

6. Health, safety, and leave: Health and safety improvements come from reduced lifting and fewer repetitive actions. The system supports supervisors by providing clear status indicators and alarm management; your teams can leave manual heavy-lifting to the robots while maintaining ability to respond quickly to exceptions. This reduces injury risk in dense layouts and supports continuous operation alongside human workers.

RaaS platform architecture and system integrations

Recommendation: Deploy a modular, API-first RaaS platform with a centralized control plane and edge compute to keep latency low and footprint lean. nasdaq-listed Berkshire Grey announces RaaS for scalable robotics solutions, and this approach prioritizes integrated workflows across inbound, putaway, picking, and outbound shipping. Use a vendor-agnostic integration layer to connect WMS, ERP, and TMS without bespoke rewrites, and design for rapid onboarding of new applications from the front end to the dock.

Architecture builds on a microservices stack with a persistent data fabric and an event-driven backbone. A centralized control plane coordinates demand signals, while edge nodes near the dock run cobots and sensing workloads to reduce latency. An integrated security model with RBAC, TLS, and audit trails protects data, and supports multi-tenant deployments with strict separation. The result is a resilient system that preserves throughput across sites and sustains an industrial robotics experience.

System integrations cover inbound and outbound workflows and cross-functional layers. Tie the RaaS platform to WMS for auto task creation, to ERP for ordering and invoicing, and to TMS for transportation planning. Build connectors that handle mexican store networks and cross-border orders with translations and currency handling. Design for cobot orchestration in grocery and general retail applications, with contact center integration for inquiries and real-time status updates. Include APIs to expose applications for developers and partners, enabling inbound inquiries and rapid ordering from merchants.

From a development perspective, keep the footprint lean by adopting containerized services and a shared data model. Align with a clear vendor roadmap and Alstine’s integration program to maintain consistency across sites. Track metrics like cycle time, yield, and robot utilization to improve and optimize. This approach keeps the experience consistent for grocery chains and industrial facilities and supports scalable deployment across multiple markets, including nasdaq and global operations.

Pricing models, service levels, and contract terms

Recommendation: Start with a tiered RaaS contract that blends a competitive fixed platform fee with usage-based charges, and embeds consulting and upgrade options to enable brands to realize stable costs while sustaining dynamic throughput.

Pricing models combine a competitive base platform fee with usage-based charges tied to parcels processed and modules activated. The base fee covers the central control hub and the product’s core modules, while per-parcel rates decrease as volume rises across bands (for example 0–10k, 10k–50k, and 50k+ parcels monthly). Add-on modules include enhanced analytics, automated replenishment, sortation, and outbound/inbound workflows. A consulting package accelerates network design, line balancing, and workforce planning, enabling your team to realize faster ROI.

Service levels are offered in three tiers: Gold, Silver, and Bronze. The central SLA targets uptime of 99.9% monthly and a clear MTTR path: Gold 4 hours, Silver 12 hours, Bronze 24 hours. On-site response windows range from 2 business days for Gold to 7 business days for Bronze. Data access includes retrieval of operational data with weekly dashboards and monthly exports of retrieved metrics. A human-in-the-loop option is available for exception handling, while the automated system continues to operate at high performance. All tiers include dedicated consulting team support for optimization and changes in flows as volumes rise.

Contract terms favor long-term partnerships with clarity: 3- to 5-year terms with possible renewal options and a defined change-control process for scope or module additions. Price escalators tied to CPI or fixed 2–3% annual increases are disclosed up front. Exit rights cover data retrieval, export of configurations, and transition assistance to an alternate provider, ensuring the entire handover is seamless. Intellectual property around custom configurations remains with the client, while Berkshire Grey retains rights to the standard platform libraries.

Product strategy centers on an integrated platform that anchors all operations in a central workspace. Modules span picking, packing, sortation, palletizing, inbound/outbound, and yard management, with tight ERP/WMS integration. Enterprises can manage changes via a single interface, enabling unified visibility across brands and facilities. Performance dashboards and retrieved performance data drive continuous improvement for the human and automated team alike, while new generation robots plug into the existing modules without disruptive deployment.

Commercial approach emphasizes flexibility and value: multi-site deployments qualify for volume discounts, while standard terms reduce risk for both sides. Bundled services mix consulting, training, and ongoing optimization into a single commercial package, ensuring every parcel operation–from parcels to pallets–operates with enhanced efficiency. A general framework supports changes in volume, SKUs, and network design, ensuring the solution scales with your business needs.

Adopting this structure increases predictability, strengthens the performance trade-off for all parties, and enables rapid iteration as your automation strategy matures.

Security, data privacy, and regulatory considerations

Adopt privacy-by-design with auditable controls across all bgry RaaS deployments, and establish a clear shared responsibility model between Berkshire Grey and customers. Define who handles data, who addresses incidents, and how access is granted, ensuring accessible, ai-enabled capabilities are safeguarded without complicating operator workflows.

Address uncertainties in data flows by implementing data minimization, pseudonymization, and encryption at rest and in transit. Build data-flow diagrams for warehousing environments, clearly separating health data and other sensitive information, and maintain immutable audit logs to support traceability. Protect trademarks and other IP assets as part of the platform’s governance, so the solution remains trustworthy for both operations teams and business leaders.

Regulatory alignment requires mapping controls to GDPR/UK GDPR, CPRA, HIPAA where health data are involved, and sector-specific standards for supply chains. Use DPIAs where applicable and define data-residency paths for cross-border transfers. Maintain a formal vendor risk management process for third-party technologies and cloud services integrated into the solution, and keep data-processing agreements up to date with incident-notification commitments and escalation paths.

Security and governance prioritize identity, access, and data protection across all activities. Implement MFA, RBAC, and just-in-time access for critical functions, with encryption of data at rest and in transit and routine key rotation. Maintain comprehensive audit trails and deploy ongoing threat monitoring, vulnerability management, and regular penetration testing. Align training and operational practices with growth plans to improve people readiness and technology knowledge, addressing ongoing changes in technologies and processes across warehousing and logistics sites.

Paths to sustained compliance require transparent documentation, accessible policies, and straightforward data-control options for customers. Provide clear data-access requests, consent-management capabilities, and deletion workflows, supported by incident response playbooks with defined roles and timescales. Classify data into special categories where necessary and apply enhanced protections accordingly, while safeguarding your trademarks and brand integrity in all customer-facing agreements and data-use terms.

Pilot programs, rollout timelines, and customer onboarding steps

Launch a three-site pilot with a 4-week ramp and a 6-week evaluation window to prove ROI. Establish a central program management office, align with customer requirements, and use a same baseline across locations. This approach yields better outcomes by data routed from on-site sensors to the edge computer and central service layers, enabling rapid feedback and reducing uncertainties. The plan could accommodate andor alternative configurations if a site underperforms.

Deploy three automation levels: basic for routine picking and lifting, enhanced for heavier lifts and higher traffic, and optimized for cubic throughput. Each level uses standardized hardware and software modules so the same configuration can be found across sites while remaining unique to the environment. Scanned barcodes and real-time sensors feed a computer-based control loop, routed to a central service layer, with asrsshuttles moving totes between zones. This structure supports a part-by-part ramp and gives management visibility into bottlenecks.

Rollout unfolds in three phases: Phase 1 covers site prep, training, and integration (4 weeks); Phase 2 runs live operations with a controlled order mix (6 weeks); Phase 3 expands to additional lines and product families (8 weeks). The timeline targets 2-3 weeks for onboarding a given site, with weekly reviews to track time-to-value and adjust assumptions. Use a shared dashboard to monitor throughput, error rate, and uptime; aim for a 15-25% time gain per site year over year.

Step 1: Kickoff with stakeholders to align objectives, safety, and data sharing.

Step 2: Baseline data scan and network readiness to confirm traffic routes and bandwidth.

Step 3: System integration mapping and compatibility checks with scanned inventories.

Step 4: Operator training and change management plan to ensure smooth adoption.

Step 5: Cutover to live operations with a staged handover and dashboards for ongoing monitoring.

Step 6: Post-implementation review to capture learnings and feed back into the next rollout.

To handle uncertainties, implement a risk plan with clear acceptance criteria, escalation paths, and a reserve of spare parts. Maintain at least two backups for critical components and ensure data privacy in each environment. Track metrics such as better throughput and reliance on automation; monitor central service performance and adjust requirements as needed. After onboarding, formalize a continuous-improvement loop so customers can realize more value from the service.