Frontier models are the engine. We build the vehicle.
Eight industries. One factory. Production agents tuned to the physics of your business — margin, availability, SLA, working capital — deployed on your stack, governed by design
Executive Data Infrastructure as a Service
Most enterprise leadership teams are running on fragmented truth. The finance team ispulling numbers from one system, sales team from another, and the operations team from athird, each having different definitions, different refresh rates, and different owners. Theresult is endless reconciliation meetings, delayed decisions, and zero confidence in board-level reporting. The data exists but the insight and value from it is lost in the fine print.
We build a governed, executive-grade semantic layer deployed directly on your existing cloudinfrastructure - Snowflake, Databricks, Azure, AWS or GCP. There are no forced migrations,and no ripping out what works. We connect to every source system (Oracle, SAP, Salesforce,NetSuite, custom ERPs), unify entity definitions (what is a 'customer', a 'product', a 'region'),apply lineage and quality controls, and deliver a single source of truth that executives cantrust and auditors can verify.We map influence, narrative, and relationships across the open web at internet scale. Our Deep Social Graph links people, companies, topics, and events whilst surfacing connections, narrative trajectories, and risk signals that can't be seen from any single source. On top of media monitoring, we present structured relationship intelligence, deployed as a governed, query-able data product on your stack.
The result? We don’t just deliver a dashboard. We give you a governed semantic foundationthat powers both analytics and AI agents, so every metric means the same thing,everywhere, always.
Capabilities
Semantic layer deployed on Snowflake / Databricks / Azure / GCP / AWS
Connectors to Oracle, SAP, Salesforce, NetSuite, custom ERPs, and finance systems
Entity resolution across products, customers, locations, and suppliers
Role-based access control (RBAC), data lineage, and full audit trail
Board-ready KPI dashboards with consistent, governed definitions
Foundation layer that plugs directly into vdd.ai AI agents
Results
Quiet Momentum
Single source of truth across all executive reporting
Reduced time-to-insight for leadership decisions (days of work turn into hours)
1,200+
Satisfied Businesses
Consistent KPIs across business units and geographies
Audit-ready reporting from day one
Reduced data team overhead spent on reconciliation
Deep Social Graph Insights
The internet is a live signal. It’s constantly changing and evolving but enterprise teams can't read it on a scale and miss relationship networks until it's too late. Investment researchers manually track narratives across thousands of sources. Risk teams find out about reputational exposure after it surfaces in the press. There is a gap between intelligence and the infrastructure to capture, map, and act on it.
We map influence, narrative, and relationships across the open web at internet scale. Our Deep Social Graph links people, companies, topics, and events whilst surfacing connections, narrative trajectories, and risk signals that can't be seen from any single source. On top of media monitoring, we present structured relationship intelligence, deployed as a governed, query-able data product on your stack
.For investment teams, this means dealing sourcing signals before relationships are public. For strategy teams, this means competitive narrative mapping in real time. For risk teams, it means early warning on reputational exposure, executive relationships, and market sentiment shifts.
Capabilities
Internet-scale entity graph linking people, companies, topics, and events
Narrative tracking (how a topic or entity is being framed, and how that changes)
Relationship mapping for due diligence and deal sourcing
Competitive intelligence (how competitors are positioning and who is talking about them)
Risk signal monitoring (reputational exposure, regulatory narrative, leadership changes)
Delivered as a governed data product on Snowflake / Databricks / Azure / GCP / AWS
Results
Quiet Momentum
Earlier deal sourcing signals, surface opportunities before they're snagged by competitors.
Richer due diligence about relationship networks, narrative history, key influences
1,200+
Satisfied Businesses
Real-time competitive narrative monitoring
Proactive narrative risk management (known before it reaches the press)
AI Pricing Copilot
Pricing decisions are being made too slowly, with incomplete data, and without a systematicview of the competitive landscape. Retailers are reacting to competitor price moves hours ordays late. This leads to promotional budgets being allocated based on gut, not signal.Furthermore, bundle and assortment opportunities are invisible. The margin war is beingfought with spreadsheets.
We deploy an AI agent that monitors competitor prices, promotional activity, bundlestructures, and assortment moves at internet speed, and then synthesizes that signal withyour own margin structure, inventory position, and sales velocity to surface actionablepricing decisions. We’re not talking about recommendations on a dashboard that get ignoredbut decisions with context, guardrails, and integration into your pricing workflow.
Capabilities
Real-time competitor price monitoring on web, dark stores, and quick commerceplatforms
Promotional intelligence encompassing competitor promo patterns, timing, depth, andcategory targeting
Dynamic bundling and assortment gap analysis
Margin-aware recommendation engine
Surge pricing logic for demand-sensitive SKUs or categories
Integration into existing pricing tools, ERP, and merchandising systems
Results
Quiet Momentum
Margin uplift through faster, more accurate competitive response
Reduced promo leakage, when budget is spent where it moves volume, not where itwas always spent
Faster competitive response time in hours, not days
Improved conversion through dynamic bundle and assortment optimization
AI Stock Copilot
Stock decisions are made with stale data, siloed systems, and rules built for last year's demand patterns in a world that is thinking 10 years ahead. Stockouts erode revenue as well as customer trust. Overstock ties up working capital and creates markdown pressure. Manual replenishment processes can't keep pace with demand volatility. The inventory is there but it's just in the wrong place. That’s where we come in.
We deploy an AI agent that continuously optimizes stock performance across the full availability loop, replenishment forecasting at SKU level, assortment optimization by store or channel, and purchase order planning aligned to actual demand signals. The agent connects to your ERP, WMS, POS, and supplier systems, learns demand patterns at granular levels, and surfaces decisions before stockouts happen, not after.
Capabilities
Replenishment forecasting at SKU, location, channel level
Assortment optimization making sure the right products are at the right stores in the right quantities
Purchase order planning with lead time and supplier reliability modeling
Stockout and overstock early-warning system
Working capital impact modeling so you can see the cash effect of inventory decisions
Integration with ERP (SAP, Oracle), WMS, POS, and supplier EDI
Results
Quiet Momentum
Reduction in stockout frequency and lost sales
Freed working capital through leaner, better-positioned inventory
Sales Report
$9,134
+2.5%
Lower overstock levels and reduced markdown pressure
Reduced data team overhead spent on reconciliation
AI Shipment & Routing Optimization Agent
Most routing systems are built on yesterday's constraints. They optimize for a staticsnapshot built on planned routes, estimated times, assumed capacity. And they all fall apartwhen reality deviates, which it always does. Traffic changes, roadblocks (literal ones),capacity shifts, service windows tighten – all these results in missed SLAs, inflated deliverycosts, and fleet inefficiency that compounds daily.
We deploy a real-time geospatial and predictive optimization agent that continuouslyrecomputes routing under live constraints not as a one-time plan but as a continuousdecision loop. The agent ingests live traffic signals, capacity data, service windowcommitments, and historical performance patterns to optimize across the full network: lastmile, hub-to-hub, carrier allocation, and fleet utilization.
Capabilities
Dynamic route optimization under live constraints, be it traffic, weather, capacity,service windows
Predictive service-window alerting which flags SLA risk before it becomes a breach
Fleet and carrier allocation optimization to bring miles down, utilization up
Network-level optimization across hubs, regions, and third-party carriers
Historical pattern learning that improves over time as the agent learns your network
Integration with TMS, WMS, carrier APIs, and fleet management systems
Results
Quiet Momentum
Reduced delivery cost per order with fewer miles, and better load factors
Improved SLA performance with fewer late deliveries, and even fewer penalties
Sales Report
$9,134
+2.5%
Better fleet utilization to reduce empty miles and idle capacity
Network-level visibility across all carriers and routes
AI Shipment & Routing Optimization Agent
Most routing systems are built on yesterday's constraints. They optimize for a staticsnapshot built on planned routes, estimated times, assumed capacity. And they all fall apartwhen reality deviates, which it always does. Traffic changes, roadblocks (literal ones),capacity shifts, service windows tighten – all these results in missed SLAs, inflated deliverycosts, and fleet inefficiency that compounds daily.
We deploy a real-time geospatial and predictive optimization agent that continuouslyrecomputes routing under live constraints not as a one-time plan but as a continuousdecision loop. The agent ingests live traffic signals, capacity data, service windowcommitments, and historical performance patterns to optimize across the full network: lastmile, hub-to-hub, carrier allocation, and fleet utilization.
Capabilities
Dynamic route optimization under live constraints, be it traffic, weather, capacity,service windows
Predictive service-window alerting which flags SLA risk before it becomes a breach
Fleet and carrier allocation optimization to bring miles down, utilization up
Network-level optimization across hubs, regions, and third-party carriers
Historical pattern learning that improves over time as the agent learns your network
Integration with TMS, WMS, carrier APIs, and fleet management systems
Results
Quiet Momentum
Reduced delivery cost per order with fewer miles, and better load factors
Improved SLA performance with fewer late deliveries, and even fewer penalties
Sales Report
$9,134
+2.5%
Better fleet utilization to reduce empty miles and idle capacity
Network-level visibility across all carriers and routes