GTM intelligence tools that change how infrastructure is bought, and production AI systems built to run in regulated environments. Live and accepting demos — reach out if you want to know what’s in the pipeline.
GPU selection and workload-matching tool for GPU rental and cloud providers. Profiles buyer workloads (model size, context, throughput SLO) and maps them to the provider’s GPU catalog with cost-per-token for each fit.
See how it works →A browser-only sizing tool that maps an AI inference workload (model, precision, context, concurrency, latency SLO) to a specific NVIDIA GPU count, topology, and Dell or HPE server configuration. Every number is physics-derived and traceable — VRAM, throughput, and power/cooling computed from formulas and model-card data, not lookup tables.
Request a demo →A browser-based data-foundation-readiness assessment tool that scores a prospect across 6 dimensions (data quality, accessibility/integration, governance, infrastructure capability, AI retrieval readiness, AI output governance) via a 29–53 question assessment (Quick/Advanced modes), producing a prioritized gap report with PDF export.
Runs real inference load against hardware a team is evaluating and surfaces the measurements that tend to shape the purchase decision — quantization tradeoffs, context window limits, sustained load behavior, and concurrency ceiling. The team comes away with a clearer sense of what a given device can handle before they commit.
Request a demo →A browser-based facility-readiness assessment for GPU cluster deployments. Buyers walk a four-step wizard (cluster, space, power, cooling) against ~39 OEM server configurations while a live sidecar computes physics-derived readings — power limits, thermal capacity, rack space, floor loading, network ports, dew-point risk — producing a per-domain CLEAR/WARNING/CRITICAL verdict table with figures, suggested actions, and a printable report.
Request a demo →A browser-based sizing tool that turns an LLM inference workload into a defensible on-prem GPU fleet plan. Buyers step through workload, model, GPU, server, and facility choices and receive a physics-derived CFO Bridge Report: fleet size, power draw, capex, and cost per million tokens.
Request a demo →Automates the full KYC due diligence and onboarding sequence for financial institutions — entity data, credit ratings, sanctions screening, and PEP checks run in the correct order, risk evaluated by deterministic logic, compliance documentation generated automatically. Low and medium risk cases clear without analyst involvement; the analyst queue receives only cases that require human judgment, pre-populated with all findings.
Request a demo →A shared engine — LangGraph graph controls all routing, LLM handles retrieval synthesis — with five independently licensable products: Financial Intelligence, Compliance Intelligence, Legal Intelligence, Clinical Intelligence, and Manufacturing Intelligence. Each SKU ships with its own corpus scaffold, domain rules, and documentation as a self-contained deployment.
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