Labor is vanishing.
Aging workforces, labor shortages and wage pressure are forcing factories to do more with fewer people.
A new industrial category
Measure. Optimize. Execute. Automate. Scale.
Factories are under pressure to automate — but most still run on fragmented data, manual decisions and disconnected execution.
Aging workforces, labor shortages and wage pressure are forcing factories to do more with fewer people.
China installs in roughly 50 days what the U.S. installs in a year — while Western automation remains too slow, expert-dependent and hard to scale.
Most factories have software, but still run on fragmented data, manual decisions and automation promises that rarely scale.
Everyone wants autonomous factories.
The opportunity is not "AI for manufacturing." The opportunity is the operating intelligence layer that connects data, decisions and automation.
Machine signals, downtime reasons, cycle times, OEE, layouts and operator inputs remain fragmented across systems.
Most plants operate below their full potential — leaving major capacity, productivity and performance gains untapped.
Most factories still struggle to turn insights into automated decisions, workflows and robotics projects.
Capture factory reality
Unlock hidden capacity
Turn decisions into action
Launch robotics projects
Compound proven gains
A new category connecting factory data, optimization, execution, automation commerce and industrial reasoning into one closed loop.
Capture real factory performance
Hardware layer for machine and process data.
iot.dbr77.com →
Test decisions before CAPEX
Factory visualization and simulation tool.
dt.dbr77.com →
Turn decisions into work
Plant Operating System for workflows and tasks.
iris.dbr77.com →
Launch automation projects
Two-sided e-commerce marketplace for robotics and automation.
marketplace.dbr77.com →
Scale industrial consulting
AI-native consulting execution tool for industrial transformation.
consultify.ai →LLM trained on manufacturing and transformation data. Five tools form one loop. Vector turns factory context into decision-ready actions.
It connects factory data, industrial knowledge, transformation methodology and automation intelligence across the entire platform.
Machine signals, downtime, OEE, cycle times, operator inputs, process flows and production context.
Lean, automation, robotics, process optimization, maintenance, quality, logistics and plant operations know-how.
Digital maturity assessment, roadmap creation, initiative management, KPI tracking and value realization.
Supplier knowledge, technology matching, integrator capabilities, project specifications and implementation patterns.
A 120-billion-parameter industrial LLM, fine-tuned on real factory transformation cases.
Turns fragmented factory data and operational context into structured intelligence.
Suggests optimization actions, automation opportunities and next-best decisions.
Transforms recommendations into workflows, tasks, owners, milestones and follow-ups.
Turns every project, deployment and factory interaction into reusable industrial knowledge.
DBR77 turns factory data into one execution loop for productivity, automation, and resilience.
Recurring software + automation transactions + usage-based AI.
SaaS lands. Marketplace monetizes. Tokens scale.
Recurring platform access
"Land and expand inside the factory."
Take rate on automation CAPEX
"Monetize the automation spend created by DBR77."
Usage-based industrial intelligence
"Shift value from human work to AI execution."
Recognized pain → operational control → automation revenue.
One left-to-right motion: product entry points unlock operational control, which unlocks automation revenue at scale.
Entry products · Customer pain
We enter through clear customer pain: transformation agenda, factory planning or visible operational inefficiency.
Workflows · Data · Decisions
Once inside, DBR77 takes control of data, workflows, decisions and execution discipline.
Revenue at scale
Operational improvement turns into automation projects, marketplace transactions and usage-based AI revenue.
DBR77 enters Round A with validated products, active deployments, global customers and a scalable industrial ecosystem.
AMPC · RIYADH 2025
Legacy systems control operations. New point solutions improve fragments. DBR77 closes the full loop.
Built by industrial veterans and AI-native operators with global execution track record.
Scaled a global Tier 1 automotive group; 20+ yrs of industrial execution at C-level.
Ex-NVIDIA industrial AI leader; opens U.S. market access for DBR77.
Serial industrial entrepreneur; opens government and OEM access across DACH and MENA.
Ex-McKinsey manufacturing strategist; 16+ yrs scaling industrial automation programs.
Built DBR77's AI engineering; 9+ yrs delivering production industrial software.
17 yrs commercializing science-to-market R&D; recruits the rare industrial AI talent that scales us.
Institutional VC; lead investor in DBR77.
U.S. industrial owner-operator; opens American factory access.
Senior industrial tech operator; OEM access into Volvo Cars.
Opens Google's global tech partnership network.
Robotics OEM access into Fanuc, global automation leader.
Industrial finance partnerships at Santander Corporate.
Capital will accelerate product scale, global GTM, Marketplace growth and AI execution capabilities.
DBR77 is building the Industrial Intelligence Platform for the next era of manufacturing.
Measure. Optimize. Execute. Automate. Scale — with Industrial Intelligence.
Join us.
Book a meeting with DBR77A proprietary industrial LLM built to turn factory data into decision-ready actions — not generic chat.
Vector is not a generic LLM wrapper. It is a decision layer trained to understand factory constraints, process logic, throughput, bottlenecks, CAPEX impact and execution risk — a new category between AI assistants, digital twins and industrial operating systems.
Vector is DBR77's own industrial language model — designed for production environments, not generic office work. It uses domain-specific weights, QLoRA fine-tuning and structured reasoning paths built around industrial decision logic.
Trained on real factory transformations: operational baselines, root-cause analysis, constraints, action plans, financial impact and implementation paths. Synthetic Digital Twin scenarios extend the corpus with tested factory physics.
Vector embeds industrial reasoning primitives — MTM, Lean, Little's Law, ISO 22400, bottleneck logic, throughput constraints, cycle times and ROI. It rejects recommendations that break factory physics, operational or financial logic.
DBR77 created the Industrial Reasoning Benchmark — a framework measuring decision quality, not text generation. Scores diagnosis, feasibility, financial logic, implementation risk and consistency.
Vector can operate on-premise, through a private API or in a dedicated secure cloud. Client data never trains the shared model. Every recommendation is versioned, audited and traced back to decision logic.
DBR77 is already moving through deployment, expansion and signal stages across global manufacturing markets.
After Hitachi Energy took over the former ABB plant in Łódź, DBR77 used Digital Twin to optimize two production halls and open the path to automation.
DBR77 built a Digital Twin of the production plant to visualize operations, test layouts and validate logistics flows before physical changes. The model helped improve the layout across two production halls before the customer committed to implementation.
After the target layout was confirmed, DBR77 opened the path to source robotics and automation projects through its two-sided Marketplace. Structured welding workstation projects by connecting Hitachi Energy with system integrators, KUKA suppliers and a local technical university.
The successful Łódź engagement positioned DBR77 as a multi-site automation partner for a Fortune Global 500 industrial leader. Active discussions are now underway for similar Digital Twin and automation programs at Hitachi Energy facilities in Germany and the United States.
Where factory data becomes industrial decisions — and decisions become executed automation.
Logs, goals, exceptions, tasks, decisions
PLCs, SCADA, sensors, cycle times, downtime
ERP, MES, QMS, WMS, HRM, maintenance & finance
Digital Twin simulations, future-state layouts, automation options
Industrial context protocol — connects machines, systems, simulations and execution tools into one structured, bidirectional layer.
Vectorized knowledge base — factory cases, process methods, technologies, suppliers and implementation patterns.
Factory-trained LLM. Turns industrial context into diagnosis, action plans, constraints, risks and ROI logic.
Routes recommendations into product-level agents — simulations, specifications, workflows and tasks.
Learns from recommendations, simulations and execution outcomes. Improves agent playbooks.
Production Decision Agents
Transformation Execution Agents
Technology Matching Agents
Simulation & Design Agents
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