Govern every touchpoint
Across the AI software lifecycle

An AI-driven SDLC has countless touchpoints: every prompt, completion, agent action, and commit, from the IDE all the way to production. Each one is a place where a secret can leak, an unapproved model can slip in, or a policy can be broken.

OneX wraps those touchpoints in layered defense. Every interaction is observed and screened: Safety, Risk, and Policy checks catch violations at the right layer, while approved work flows clean through to the core.

One platform to observe, govern, and optimize AI across the entire lifecycle, so your developers keep moving while governance, security, and FinOps hold the line.

Get Started

From IDE to audit, in one path

Every prompt and agent turn flows through OneX, where risk is caught at the gate and spend is metered on the way through. Hover a stage to trace its path.

IDE → AI Agent → OneX → Governance & FinOps

Agent activity Violation caught Token metered

The three gaps in
AI-SDLC today

Knowing that developers use Copilot or Claude Code doesn't tell you whether API keys leaked into a prompt, an unapproved model answered a production question, or a shell command tried to exfiltrate secrets.

Vendor billing tells you what you spent last month, not who drove it, which IDE or project caused the spike, or whether cache-aware usage patterns could cut cost this week.

Developer AI tokens flow through Claude, Copilot, Cursor, OpenAI, and Gemini, often before procurement has a contract, before platform has a budget, and long before finance can allocate spend to a team.

OneX closes all three gaps with instrumentation at the agent surface and FinOps telemetry your CFO and your CISO can both trust.

Monitoring the AI-SDLC
efficiently & responsibly

Six pillars: Governance and FinOps elevated equally.

AI Agents

Real-time agent risk posture, not annual attestations

See every instrumented AI agent (Cursor, GitHub Copilot, Claude Code, Windsurf, Gemini CLI, Amazon Q, and more) in a single risk-ranked inventory. Track active developers, events captured, PII exposure, safety violations, and last-seen activity. Filter by critical, moderate, or low risk and drill into per-agent PII and Safety assessment cards.

OneX dashboard: AI Agents risk-ranked inventory with PII and safety posture per tool
Violations

Violation triage built for security teams

Centralize every policy finding across agents. Filter by assessment type, severity, surface, agent, and developer. Review evidence with immutable trace references, export for incident response, and suppress known false positives without turning off detection.

OneX dashboard: Violations triage list across agents with severity and filters
Detection Coverage

Detection coverage you configure, auditors can verify

Operate a full catalog of PII, secrets, regulated-data, and safety rules. Enable globally or per agent, see what's firing this month, and prove what you detect and where.

OneX dashboard: Detection Coverage catalog of PII, secrets, regulated-data and safety rules
Security Controls

Security controls that drive cascade enforcement

Define allowlists for approved models, tools, egress hosts, and client/tenant boundaries. Unlisted usage triggers structured violations: unapproved model, unapproved tool, exfiltration risk, cross-tenant boundary, all wired directly to governance posture.

OneX dashboard: Security Controls allowlists for approved models, tools, egress hosts and tenants
Policies

Policies that connect detection to action

Combine finding types, agents, developers, and surfaces into warn policies with Slack and email notifications. Turn governance from passive logging into an operational loop.

OneX dashboard: Policies with active warn rules and notifications
AI Usage

FinOps for developer AI, spend with reason

Track total, input, cache, and output tokens across your organization in near real time, not when the invoice lands. Slice by provider, user, IDE, source, and project. Drill from org KPIs into individual conversations and workflow turns to answer: Who spent? On what? When did it spike? Was cache doing its job?

OneX dashboard: AI Usage and Conversations FinOps KPIs for total, input, cache and output tokens

From token telemetry to spend accountability

Production FinOps starts with inference and infrastructure. AI-SDLC FinOps starts where spend actually begins: every prompt, completion, and agent turn in the IDE. OneX brings the same operational discipline finance expects from cloud cost management to developer AI consumption.

442.1M Total tokens
226.7M Input
213.9M Cache
17,035 Events

Total tokens, the input/cache/output mix, events, and active users, each with a 24-hour trend, so spikes surface as they happen.

Compare consumption across Claude, Copilot, Cursor, OpenAI, and Gemini, filtering by provider, user, IDE, and source.

Follow any conversation turn by turn, tool calls included, with chargeback-ready attribution down to the session.

Near-real-time polling keeps usage current, so stakeholders see spend move as developers work.

Same platform as FinOps for Models: training, inference, and infrastructure. Govern risk at the keyboard; optimize spend to production.

Your developers should move fast,
Your governance and FinOps should keep up

Bring agent risk posture, violation triage, detection coverage, security allowlists, warn policies, and org-wide developer AI FinOps into one enterprise observability platform, from the IDE to production inference.

Get Started