Provider ecosystem
ANAnthropic
GGGemini
XAxAI
MIMistral
OROpenRouter
OAOpenAI
Enterprise AI Control Plane
Governed AI Operations For Enterprise Scale
Governed access across models, providers, tools, and workflows
Runtime guardrails with monitor and enforce modes
Evidence-ready telemetry for security, finance, and compliance
ThinkNEO unifies governed model access, runtime safety, deep observability, compliance readiness, agent control, and AI FinOps in one operational layer.
Tracks real usage across providers
Enforces budgets and policy controls
Generates audit-ready governance logs
Illustrative governance dashboard
thinkneo.ai/dashboard
Live
Total Spend
$21.3k
Requests
88.6k
Blocked
746
Compliance
61%
Spend Over Time-12% vs last month
Live Requests
streaming
AI Provider Agnostic by Design
Production-ready adapters across leading AI providers: OpenAI • Anthropic • Google Gemini • xAI • Mistral • OpenRouter.
ANAnthropic
GGGoogle Gemini
XAxAI
MIMistral
OROpenRouter
OAOpenAI
DSDeepSeek
MLMeta Llama
COCohere
CLClaude
ANAnthropic
GGGoogle Gemini
XAxAI
MIMistral
OROpenRouter
OAOpenAI
DSDeepSeek
MLMeta Llama
COCohere
CLClaude
Switch providers without changing governance workflows
Normalize cost and telemetry across vendors
Keep one policy surface across providers
ThinkNEO Governance Layer
ObservabilityGovernanceRoutingPromptOpsGuardrailsAI FinOps
routing · policy scope · guardrails
telemetry · attribution · budget enforcement
Runtime outcomes
routing · policy scope · guardrails
telemetry · attribution · budget enforcement
One control surface across changing vendors
One
governance layer
Unified policy surface across providers.
Zero
vendor lock-in
Provider routing stays independent from governance.
Full
enforcement
Controls execute inline on every request.
91%
"Governance should not depend on your AI vendor.
It should sit above it."
01ThinkNEO connects through secure native adapters.
02Budgets, attribution, audit logs, and policy are enforced on every request.
03Governance stays stable while providers evolve.
How It Works
How It Works
Deploy ThinkNEO as an enterprise AI control plane in four operational phases.
Unified Access Pattern
Introducing The Enterprise AI Control Plane Pattern
Your AI Apps
ThinkNEO Control Plane
Observability
Governance
Routing
PromptOps
Guardrails
AI FinOps
Multi-Provider Models
OPOpenAI
ANAnthropic
GOGoogle
XAxAI
MIMistral
OPOpenRouter
DEDeepSeek
COCohere
MEMeta
Custom Models
Fine-Tuned Models
AI provider agnostic by design — production-ready adapters
01
Connect applications and providers
Keep existing app flows and provider endpoints while routing through one governed control layer.
02
Apply policy-aware routing
Route by model, provider, workload, and risk profile with consistent control boundaries.
03
Enforce runtime guardrails
Run input/output/context/tool controls in monitor mode first, then enforce for active protection.
04
Operate with observability and FinOps
Use traceability, evidence workflows, and cost-quality analytics to scale with accountability.
Every request is evaluated in the runtime path for routing intent, policy scope, guardrail posture, telemetry capture, and budget impact.
Governance Outcomes
What Enterprises Measure With ThinkNEO
Enterprise teams evaluate governance by operational outcomes that can be reviewed and repeated across security, platform, and finance workflows.
Policy decisions tracked
Each request is evaluated against routing intent, policy scope, and runtime guardrail posture.
Runtime control signal
High-risk requests escalated or blocked
Risk-aware controls run before downstream model and tool execution to reduce unsafe behavior.
Safety and governance signal
Spend anomalies surfaced
Cross-provider telemetry helps finance and platform teams investigate cost drift early.
AI FinOps signal
Investigation timelines reduced
Unified evidence trails shorten handoffs between engineering, security, and compliance.
Operational evidence signal
Representative outcomes shown on this page. Customer-specific evidence is shared during enterprise review.
Enterprise Buyers
Built For Teams Governing AI In Production
ThinkNEO is designed for organizations that need runtime control, accountable operations, and review-ready governance signals across technical and executive stakeholders.
CTO / Head of AI
Needs one control layer across providers without rewriting product stacks.
Unifies governance, runtime controls, and provider strategy in one operational model.
Architecture and rollout confidence
Security & Compliance
Needs traceable policy enforcement and audit-ready evidence under active workloads.
Adds runtime guardrails, evidence trails, and security review workflows.
Reviewable governance posture
Platform Engineering
Needs stable provider routing and observability without fragmented tooling.
Standardizes control points for routing, telemetry, and runtime decisions.
Operational reliability at scale
Finance / AI FinOps
Needs cost attribution and budget discipline across teams and providers.
Connects spend visibility with policy controls for accountable AI economics.
Clear spend accountability
Customer references and verified outcomes are shared as part of enterprise evaluation workflows.
AI Financial Risk
AI Adoption Without Governance Is Financial Risk
As organizations scale AI usage, costs become unpredictable, attribution becomes unclear, and compliance turns reactive. Multi-provider environments multiply this risk.
The core gap is not model quality alone. It is missing control-plane discipline across runtime safety, observability, governance, and economics.
Runtime safetyDeep observabilityGovernance workflowsEconomic accountability
Illustrative uncontrolled environment
Costs become unpredictable
Waste exposure trend
Teams create uncontrolled API keys
Unmanaged API key growth
Attribution becomes unclear
Attribution blind spots
Finance loses visibility
Finance visibility gaps
Without governance
- ✕ No real-time spend attribution
- ✕ No budget enforcement
- ✕ No cost anomaly detection
- ✕ No provider comparison
- ✕ No accountability trail
With ThinkNEO governance
- ✓ Department-level attribution
- ✓ Hard budget enforcement
- ✓ Model and policy controls
- ✓ Unified provider visibility
- ✓ Immutable audit-ready records
Strategic Differentiation
Beyond Proxy, Beyond Gateway, Beyond Point Tooling
ThinkNEO is not a single-function layer. It is the enterprise operating system for AI runtime control, policy accountability, and economic governance in production.
Control Plane, Not Just Routing
One policy surface across providers, models, tools, and workflows.
Runtime Governance
Guardrails, enforcement decisions, and operational response in live traffic.
Economic Accountability
AI FinOps with attribution, budget controls, and spend governance by context.
Enterprise Evidence
Audit-ready records for security, compliance, and executive decision workflows.
Platform Capability Model
ThinkNEO Is The Enterprise AI Control Plane
ThinkNEO extends beyond gateway routing. It provides governed access, runtime safety, deep observability, compliance readiness, agent control, and AI FinOps optimization across models, providers, tools, workflows, and deployment environments.
Positioning Clarity
Not just a proxy, gateway, or cost console
ThinkNEO keeps strong gateway economics while adding runtime controls, operational evidence, and governance workflows required for enterprise AI programs.
A governed control plane for enterprise AI
Policy and economic controls are applied consistently before execution, while traceability and evidence remain available for engineering, finance, security, and compliance teams.
Multi-Provider Usage Normalization
Unified tracking across OpenAI, Anthropic, Google, xAI, Mistral, OpenRouter, and OpenAI-compatible endpoints.
Provider-Specific Adapter Layer
Handles authentication quirks, rate limits, metadata normalization, token accounting differences, and error mapping.
Department-Level Cost Attribution
Tag and assign usage by team, project, workspace, and cost center.
Budget Enforcement
Apply hard caps, soft alerts, and auto-block rules before spend escalates.
Model Policy Controls
Allow or deny specific models per workspace, team, or environment.
Real-Time Monitoring
Live dashboards for finance and operations teams with immediate usage visibility.
Audit Trails
Immutable request logs with timestamp, model, cost, and user metadata.
OpenAI-Compatible Gateway
Drop-in base URL replacement with no provider SDK rewrite required.
Rate Controls & Guardrails
Apply usage guardrails by key, team, and environment to prevent overrun incidents.
Workspace Governance
Tenant-aware isolation with configurable policy and budget boundaries.
Deep-dive modules
Security & Compliance
Built for Enterprise Governance
Governance without data exposure, designed for enterprise security review.
Tenant Isolation
Isolated tenant architecture with strict workspace boundaries.
Role-Based Access Control (RBAC)
Controlled access by role and workspace-level permissions.
Immutable Usage Logs
Immutable per-request event history for audits and investigations.
Encrypted Key Storage
Secure handling and storage of provider API credentials.
Exportable Audit Reports
Structured governance records ready for finance and compliance workflows.
SIEM-Ready Logs
Streamable event data for enterprise monitoring and detection systems.
SSO-Ready Architecture
Architecture prepared for enterprise identity and access integrations.
SOC 2 Alignment
SOC 2 Type II alignment in progress.
Runtime Guardrails
Input, output, context, and tool-use controls with monitor and enforce operating modes.
Contextual Data Security
Sensitive context controls for contracts, source code, pricing, and internal knowledge paths.
AI Governance Workflows
Operational workflows for risk review, evidence capture, and policy approval accountability.
Agent Action Controls
Governed agent execution with boundaries, approvals, and traceable action records.
Security Posture
ThinkNEO does not train models. Retention of governance metadata is configurable per tenant.
Security documentation available upon request.
Enterprise Trust
Security, Compliance, And Operational Assurance
Trust signals should be explicit, verifiable, and easy to review by security and procurement teams. ThinkNEO centralizes enterprise-ready controls in one governance layer.
Available nowAvailable now
- Tenant isolation and workspace governance boundaries
- Role-based access control and policy-scoped permissions
- Encrypted key handling and controlled provider credential flow
- Audit-ready logs with SIEM-oriented export pathways
Enterprise review pathIn progress / review
- Security review package available on request
- Compliance roadmap with evidence workflows
- SSO-ready and deployment documentation (SaaS, private, hybrid where applicable)
Example governance scenario
Governance Reduces Waste
AI waste often comes from unrestricted model access, duplicate experimentation, routing inefficiency, and untracked internal usage.
Lower waste exposure
Runtime policies reduce unnecessary model usage and uncontrolled retries.
Better attribution coverage
Spend, policy events, and request metadata remain traceable across teams and providers.
Enforced budget discipline
Budget controls operate in live request paths, not only in retrospective reporting.
Without governance
- ✕Fragmented spend attribution
- ✕Reactive cost controls
- ✕Limited visibility into policy impact
With ThinkNEO governance
- ✓Department-level attribution
- ✓Budget enforcement at runtime
- ✓Unified policy and economic visibility
Representative workflow: Illustrative scenario. Actual outcomes depend on policy scope, model mix, and operational baselines.
AI FinOps maturity beyond budget blocking
- Forecasted cost trajectories per workspace, model family, and use case.
- Chargeback and showback support for departmental economic accountability.
- Waste reduction workflows that isolate low-value spend patterns.
- Cost-quality routing strategies that balance reliability, latency, and unit economics.
Plug & Govern
Integrate ThinkNEO In Minutes
Route enterprise AI traffic through a governed control plane without rewriting your stack. Keep your current SDKs and add policy, observability, and FinOps controls at runtime.Start with your existing OpenAI SDK. Switch the base URL. Keep your app logic.
OpenAI-compatible quickstart
import OpenAI from "openai";
const client = new OpenAI({
apiKey: process.env.THINKNEO_KEY,
baseURL: "https://gateway.your-domain.com/v1",
});
const response = await client.chat.completions.create({
model: "gpt-4o",
messages: [{ role: "user", content: "Summarize policy drift risk by provider." }],
});
console.log(response.choices[0]?.message?.content);Sample governance dashboard (illustrative data)
Sample Governance Dashboard (Illustrative Data)
Total Monthly Spend: $148,392 • Requests: 1,284,221 • Avg Cost per Request: $0.11 • Budget Status: 82% utilized.
thinkneo.ai/dashboard/overview
OverviewRequestsUsersProjectsModelsMonitoring AgentReportsDocsActivitySettings
Live Operations Snapshot
Acme Corporation
Real request telemetry, spend flow, and fallback posture across all providers in one place.
Total Spend
$ 28,699
Total requests:
170,843
Fallback Requests
2,053 1.2%
Operational Pulse
Success Rate
98.3%
Avg Latency
342 ms
Active alerts
4
Budget Limit$
$ 45,000
63.8% used
Alerts!
4
Active alerts
Blocked RequestsX
1,136
Policy enforcement
API KeysK
47
All secure
Fallback RequestsF
2,053
Auto-served by ThinkNEO AI
Spend Over Time
$ 47,832 Forecast:: $ 62,100
MonthlyWeeklyDaily
JanFebMar
Avg cost per request:: $ 0.168 Total requests:: 284,739
Usage by Model
gpt-4o34%
claude-3.5-sonnet26%
gemini-2.0-flash18%
mistral-large12%
Others (6)10%
Top Users
1$ 8,120
M. Chen
42,318 requests
2$ 7,340
J. Silva
38,912 requests
3$ 5,890
A. Patel
31,205 requests
Recent Projects
Prod-ChatEngine-v3Active
$ 14,230Prod-PaymentAIActive
$ 11,870Prod-DocParser-MLActive
$ 8,540Recent Alerts
!
Budget 80%
Budget: $18,000 / Monthly
!
1,893 blocked requests
Policy enforcement
i
Fallback Requests active
Fallback Requests: 3,421
Operating Model by Function
Control Plane Outcomes By Enterprise Function
See how finance, technology, security, and engineering teams operate governed AI through one shared control plane.
Run AI FinOps With Governance
Move from basic spend tracking to forecasting, chargeback readiness, risk visibility, and policy-aware economic control.
Get startedKey Outcomes
- Real-time AI cost visibility
- Forecasting inputs by tenant, workspace, and workload
- Department-level and business-unit attribution
- Enforced budgets (blocking, not just alerts)
- Chargeback/showback-ready reporting
- Reduced waste and surprise spending through runtime controls
- Audit-ready economic evidence for finance and compliance
AI Usage & Cost Governance
AI Usage & Cost Governance -- Centralized
ThinkNEO sits between your applications and AI providers to enforce governance before spend becomes risk.
Governance
Policy boundaries, role controls, and accountable workflows.
Runtime Control
Guardrails and action controls in live request paths.
Observability
Cross-provider traces, auditability, and operational evidence.
AI FinOps
Attribution, budget discipline, and spend governance.
Multi-Provider Usage Normalization
Unified tracking across OpenAI, Anthropic, Google, xAI, Mistral, OpenRouter, and OpenAI-compatible endpoints.
Provider-Specific Adapter Layer
Handles authentication quirks, rate limits, metadata normalization, token accounting differences, and error mapping.
Department-Level Cost Attribution
Tag and assign usage by team, project, workspace, and cost center.
Budget Enforcement
Apply hard caps, soft alerts, and auto-block rules before spend escalates.
Model Policy Controls
Allow or deny specific models per workspace, team, or environment.
Real-Time Monitoring
Live dashboards for finance and operations teams with immediate usage visibility.
Audit Trails
Immutable request logs with timestamp, model, cost, and user metadata.
OpenAI-Compatible Gateway
Drop-in base URL replacement with no provider SDK rewrite required.
Rate Controls & Guardrails
Apply usage guardrails by key, team, and environment to prevent overrun incidents.
Workspace Governance
Tenant-aware isolation with configurable policy and budget boundaries.
ThinkNEO Governance Layer. Routes requests, tracks real usage, enforces budgets and policies, normalizes provider metadata, and generates audit-ready logs. No provider account changes required.
White Paper capability coverage
Deep observabilityRuntime guardrailsContextual data securityRegulatory governance (AI GRC)Agent lifecycle governanceGoverned connectors and actionsPromptOps and EvalOpsIdentity and deployment controlsAI FinOps optimization
Where ThinkNEO Sits in Your Stack
Your Apps -> ThinkNEO Governance Layer -> AI Providers
1
Routes requests
2
Tracks real usage
3
Enforces budgets and policies
ThinkNEO acts as an OpenAI-compatible gateway that normalizes provider metadata and generates audit-ready logs.
The same layer governs models, providers, tools, agent workflows, and deployment boundaries with one consistent policy surface.
No changes to your AI provider accounts.No vendor lock-in.Full visibility.
Frequently Asked Questions
Everything you need to know before getting started.
Enterprise AI Control Plane
Adopt Governed AI With Runtime Control
Keep your current provider stack and applications. Add ThinkNEO as the control plane for runtime safety, observability, compliance readiness, and AI FinOps.
Built for enterprise teams that need accountable AI operations across models, tools, workflows, and deployment boundaries.
Security review available on requestDeveloper docs available nowTrust center available now