From multi‑agent orchestration and enterprise RAG to MCP integrations, fine‑tuning, and synthetic data pipelines.
We turn AI pilots into production systems.
An AI agent that manages enterprise device fleets through natural language, configuring policies, predicting failures, and resolving support tickets autonomously.
AI-powered ELD intelligence that turns hours-of-service data into natural language insights, automated DOT audit prep, and real-time driver safety alerts.
Multi-agent system for pharmaceutical root cause analysis and CAPA automation, cutting investigation cycles while maintaining FDA 21 CFR Part 11 compliance.
Autonomous agents that reason, plan, and execute complex workflows end-to-end, from IT policy management to quality investigation across regulated industries.
Coordinated agent teams that collaborate, delegate, and solve multi-step problems, running parallel investigations in pharma, fleet-wide analysis in logistics, and policy enforcement across device networks.
Enterprise retrieval pipelines that ground AI responses in your operational data: compliance regulations, device documentation, fleet telemetry, and quality records.
Connecting agents to your existing infrastructure through standardized protocols: MDM consoles, ELD hardware, TMS platforms, and manufacturing execution systems.
Domain-specific model adaptation through LoRA, QLoRA, and knowledge distillation, trained on real enterprise workflows to understand your industry language.
High-fidelity data generation from unstructured enterprise documents and rigorous evaluation pipelines that ensure accuracy before production deployment.
We build AI agents that sit inside enterprise device management platforms, turning policy configuration, compliance monitoring, and support triage into natural language workflows. Our WeGuard platform with ViVi demonstrates what agentic MDM looks like in production at scale.
We transform ELD data, GPS telemetry, and fleet operations into AI-powered intelligence layers. Natural language querying, predictive maintenance, automated compliance, and driver safety monitoring, built to integrate with existing telematics hardware and TMS platforms.
We design multi-agent systems for pharmaceutical quality operations, automating root cause analysis, CAPA generation, and deviation investigation while maintaining full FDA 21 CFR Part 11 compliance. Every AI output carries an audit trail.
We work with enterprises to assess AI readiness, identify high-ROI use cases, build production-grade systems, and establish governance frameworks. Our engagements cover the full stack, from data readiness and model selection to human-in-the-loop workflows and observability.
The end-to-end pipeline for training SLMs that understand enterprise terminology and map user intent to system operations, at a fraction of frontier model costs.
A candid walk through the architecture decisions behind our production RAG pipelines including the approaches we tried first that did not work, and why each component exists to address a specific failure mode.
Commercial fleets generate massive volumes of telemetry data from TPMS, engine diagnostics, and fuel systems. We built a predictive maintenance pipeline that turns this raw data into calibrated alerts reducing unplanned downtime by 18% and improving fuel efficiency by 12%.
Single AI agents hit hard limits in complex enterprise operations. We examine the coordination patterns, architectural trade-offs, and practical decision framework for knowing when your problem demands a multi-agent system.