- Catalog-Aware Automated Assistance Deploys conversational agents across messaging and web platforms, leveraging product lists, rules, and parameters to assist users.
- Human-in-the-Loop Routing Smooth handoff logic transitions automated interactions to human operator queues whenever a user requests direct assistance.
- Live-Linked Sales Documentation Build, edit, and reference formal quotes or contract workbooks pulling real-time data from your inventory catalog.
- Unified Pulse Dashboard Macro-level visibility into communication volumes, document generation rates, and inbound form submissions.
Practical AI Built for Real Businesses.
Four ready-to-deploy platforms—plus AI Code in development—for catalog-synced sales care, factory analytics, visual inspection, resource tracking, and agentic software delivery.
Our AI Product Suite
AI Support
Catalog-aware chats, live-linked quotes, and human handoff
AI Production
Live output metrics, target tracking, and plain-language insight
AI Vision
Open-ended detection from living subjects to material anomalies
AI Energy
Hierarchical tracking, gap-fill estimates, and balance audits
SoonAI Code
Agentic coding with codebase context and workflow integrations
AI Support
Unified Customer Care and Live-Linked Sales Documentation
An omni-channel front-office solution that unifies automated customer care with back-office documentation. Conversational AI linked to live catalog records keeps chats and formal sales records synchronized.
- Target vs. Actual Visualization Compares real-time throughput against defined baselines or plans across time dimensions and individual operational units.
- Multilingual Conversational Assistant An AI agent grounded in live operational data that answers analytical queries and forecasts performance in everyday language.
- Automated Anomaly Detection Continuously monitors data streams to flag output gaps, line imbalances, or sudden resets that suggest technical or reporting issues.
- Granular Detail Drill-Downs Provides order-level and itemized logs behind high-level data points for comprehensive root-cause analysis.
AI Production
Monitor Output, Track Targets, and Ask in Plain Language
A real-time performance and analytics workspace that monitors output metrics, tracks target compliance, and bridges raw automated tracking with human-readable textual analysis.
AI Vision
Identify, Localize, and Highlight Any User-Defined Element
A trainable computer vision foundation spanning living subjects to material anomalies. Operators define exactly what objects, behaviors, or conditions the system tracks—without hardcoded software updates.
- Open-Ended Classification Adapts to any need—detecting humans, tracking vehicles, counting assets, or identifying wildlife—from sample images and labels alone.
- Spatial & Quality Control Tracking Functions as spatial awareness for presence, occupancy, or movement—and as quality inspection for cracks, defects, or wear.
- Multi-Format Processing Analyzes still photography, short video clips, or continuous long-form recordings with equal fidelity.
- Edge & Local Deployment Runs on centralized host infrastructure or thin on-site edge hardware near cameras for low-latency, isolated processing.
- Hierarchical Site Mapping Structures measuring points into localized trees—from parent sources down to sub-units—to automatically group related data streams.
- Intelligent Gap-Filling Uses predictive learning to detect data drops or silent meters and generates sensible estimates to preserve historical totals and reports.
- Balance & Reconciliation Audits Cross-references total intake against downstream consumption branches to verify balance and catch discrepancies or losses.
- Centralized Analytics Dashboard A web console to define date ranges, launch analysis workflows, view node layouts, and browse past reports.
AI Energy
Compare Input vs. Output Across Complex Monitoring Networks
An intelligent tracking and reporting system for high-consumption environments. Structures data into parent-child trees to compare intake and output balances across multiple points over custom timeframes.
AI Code
Codebase-Aware AI for Planning, Editing, and Shipping Faster
An agentic development workspace that maps dependency graphs across large repositories, breaks complex work into reviewable task lists, and proposes multi-file edits—with native hooks into GitHub, Jira, Linear, and your existing toolchain.
- Context Engine Analyzes dependency graphs, historical changes, and repository structure across massive codebases to deliver highly relevant, codebase-wide suggestions.
- Task Lists Automatically breaks complex feature requests or tickets into manageable, step-by-step plans you can review, edit, or execute sequentially.
- Suggested Edits Finds and proposes cascading changes across multiple files when a modification in one area impacts others downstream.
- Native Integrations Connects directly with GitHub, Jira, Linear, Notion, and Slack—plus multimodal input from mockups and design files to accelerate UI work.
Ready to put your operations on autopilot?
Speak with a software architect to see which system fits your company.