WrangleAI
WrangleAI is an enterprise-grade platform that gives organizations visibility, control, and governance over their AI usage and spending. It acts as a “control plane” for generative-AI tools (like GPT-4, Claude, Gemini, and more), providing real-time usage tracking across providers, cost intelligence, infrastructure monitoring, and spend caps so companies can avoid runaway budgets. WrangleAI offers AI observability, helping teams understand which models are being used, by whom, and for what purposes, plus routing intelligence that can redirect workloads to more cost-effective models while maintaining output quality. It also includes governance features such as role-based access control and compliance support (e.g., for SOC 2 / ISO 27001 standards), enabling finance, engineering, and leadership teams to coordinate, enforce policies, and get actionable recommendations for optimizing AI spending and usage.
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Cloptima
Cloptima is an AI and cloud FinOps platform that brings LLM spend governance, multicloud cost intelligence, Kubernetes optimization, query analysis, and engineering cost controls into one operating model. Its AI gateway lets teams use their own OpenAI, Anthropic, Gemini, Vertex AI, and Amazon Bedrock credentials behind encrypted controls, then apply virtual keys, model policies, token limits, budgets, guardrails, and attribution before calls reach providers. Spend analytics break down usage by provider, model, team, application, environment, user, agent session, tool, workflow, and dimensions, while agent controls track retries, loops, tool calls, and runaway-cost risk. Exact and semantic response caching can reduce repeated usage, and intelligent routing can shift eligible traffic to cheaper or faster models with canary rollout and rollback if quality, latency, or errors regress.
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AI Cost Board
AI Cost Board is an AI API observability and cost control platform that brings costs, requests, tokens, latency, errors, and usage from multiple model providers into one real-time dashboard. Applications route LLM traffic through a single proxy endpoint, while requests are forwarded to the connected provider and logged with model, token, status, timing, costs, input, output, and raw JSON context. In most cases, teams only replace the provider base URL and use an AI Cost Board project key, keeping the original request structure intact. It supports providers including OpenAI, Anthropic, and Google Gemini, with a consistent setup that standardizes usage data across integrations. Cost analytics break spending down by project, provider, model, and timeframe, showing trends, cost per request, success rates, and operational performance. Searchable request logs help developers inspect payloads, troubleshoot failures, compare models, and investigate slow or expensive calls.
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SatGate
SatGate is an agent authority and accountability Layer that governs what AI agents can access, spend, delegate, and execute before a request reaches an API, model, MCP tool, or paid external service. Deployed as an HTTP reverse proxy and MCP proxy, it applies scoped authority, per-agent budgets, route policies, and next-request revocation directly in the request path. Agents badge in once through existing Kubernetes, AWS, or OIDC identity, and SatGate Mint exchanges that identity for a cryptographically signed Macaroon containing limits for scope, budget, expiration, and delegation depth. Capabilities can only become more restrictive as they move through agent chains, preventing sub-agents from escalating beyond the authority they receive. Observe mode measures requests and attributes usage by agent, team, tool, route, and cost center without changing workflows; Control mode enforces hard budget caps before expensive or unauthorized work executes.
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