Question 1

What is Cognocient?

Accepted Answer

Cognocient is an AI spend decision intelligence platform. It proxies every LLM API call your application makes — to OpenAI, Anthropic, Google Gemini, and other providers — and attributes every dollar to a feature, team, model, or user in real time. Engineering teams see which features drive cost spikes. Finance teams get board-ready PDF reports. CFOs can answer the board question: what is our AI ROI?

Question 2

How does Cognocient work?

Accepted Answer

Setup takes 2 minutes and requires zero code changes to your application. You point your AI API calls at the Cognocient proxy URL instead of the provider directly. Optionally add X-Cost-Feature and X-Cost-Session headers to tag spend by feature or workflow. Every call is then observed, attributed, and surfaced in a real-time dashboard with anomaly detection, budget enforcement, and one-click optimization recommendations.

Question 3

Which AI providers does Cognocient support?

Accepted Answer

Cognocient supports 7 AI providers out of the box: OpenAI, Anthropic, Google Gemini, Azure OpenAI, Mistral AI, Groq, and Together AI.

Question 4

Does Cognocient optimize GPU or cloud infrastructure costs?

Accepted Answer

No. Cognocient covers AI API spend only — OpenAI, Anthropic, Google Gemini, Mistral, Groq, and similar providers billed by token. It does not optimize GPU instances, cloud compute, or Kubernetes infrastructure. For GPU and infrastructure cost optimization, pair Cognocient with your cloud provider's native tools or a cloud FinOps partner. Cognocient and infrastructure-focused FinOps tools solve different problems and work well together.

Question 5

What types of AI waste does Cognocient detect?

Accepted Answer

Cognocient automatically detects 5 categories of AI waste: (1) Context Bloat — multi-turn apps sending 40–60% redundant tokens in conversation history on every call; (2) Retry Waste — failed API calls retried within seconds and billed twice; (3) Model Mismatch — using frontier models for simple classification or summarization at up to 95% extra cost; (4) Cache Misses — identical prompts hitting the API fresh every call when a 75–90% discount is available; (5) Context Starvation — consecutive calls from the same feature that escalate in size because too little context was sent up front.

Question 6

How is Cognocient different from LLM observability tools like Langfuse, LiteLLM, or Helicone?

Accepted Answer

LLM observability tools like Langfuse are built for engineers debugging prompts and traces — they record what happened after the call. LiteLLM is an open-source gateway with routing and basic budget limits but no CFO output layer. Cognocient adds real-time pre-call budget enforcement, graceful model degradation (auto-switch to a cheaper model rather than a hard block), board-ready PDF reports with AI-written narrative, cost per business outcome tracking, investment vs. waste classification, FOCUS-aligned export for FinOps platforms, and an AI Efficiency Score as a board-level KPI. Cognocient and Langfuse are complementary — Langfuse for engineering observability, Cognocient for finance governance.

Question 7

Why does Cognocient use a proxy instead of read-only API access?

Accepted Answer

Some AI cost tools connect via a read-only API key and poll your provider's billing data on a schedule. That's a legitimate, lower-friction approach — no code changes — but it can only report spend after the fact and cannot enforce a budget before a call happens, since it never sits in the request path. Cognocient uses a proxy specifically because pre-call enforcement — blocking, degrading to a cheaper model, or alerting before the provider bills you — requires being in that path. The tradeoff is real: a proxy requires a one-line code change and adds measured latency of roughly 2-8ms at the median under light concurrency (see our published benchmark and methodology at /docs/latency-benchmark — including the honest caveat that overhead grows at high concurrency to a single instance today). If Cognocient's own budget-check layer becomes unreachable, it fails open by default — your calls pass through to your AI provider unaffected rather than being blocked, so a Cognocient outage never breaks your production AI features, though you temporarily lose enforcement and attribution data for that window (individual budgets can opt into fail-closed instead). If you only need after-the-fact reporting and want zero integration change, a read-only polling tool may be the simpler fit. If you need to stop a runaway agent loop before it finishes, or enforce a budget before spend happens, that requires sitting in the request path.

Question 8

Does Cognocient support multi-agent and MCP workflows?

Accepted Answer

Yes. Cognocient supports MCP (Model Context Protocol) and A2A (Agent-to-Agent) attribution. Pass X-Cost-MCP-Server and X-Cost-Parent-Run-Id headers to get a full workflow cost tree — showing which agent called which tool and what each step cost. You can set per-run budgets to stop runaway agent loops before they generate surprise bills, with graceful degradation for read operations and hard stops for write operations. A configurable retry/handoff depth limit also catches a runaway recursive handoff chain independent of budget — see /docs/guardrails.

Question 9

How does Cognocient handle high-concurrency multi-agent runs?

Accepted Answer

When multiple subagents run concurrently within the same orchestrated task, per-call budget checks alone cannot catch runaway spend because each individual call can look reasonable while the run as a whole exceeds any sane ceiling. Cognocient enforces a separate run-level budget reservation, shared atomically across every subagent call in a run via the X-Cost-Run-ID header, so a run with many concurrent subagents cannot collectively exceed its declared budget even though no single call ever does. A configurable maximum handoff depth independently catches a runaway chain of subagent handoffs even when no single call is expensive. Note that Cognocient itself currently runs as a single worker process per instance, so very high request concurrency against one instance adds its own latency — see /docs/latency-benchmark for measured numbers.

Question 10

How much latency does Cognocient add to my AI calls?

Accepted Answer

A real, published benchmark (methodology and raw numbers at /docs/latency-benchmark) measured added latency of roughly 2-8ms at the median for light concurrency (1-10 simultaneous requests to a single instance) — covering authentication, spend attribution, and the atomic pre-call budget reservation. That overhead grows substantially at high concurrency to a single instance (50-100 simultaneous requests) because the backend currently runs as a single worker process; this is disclosed in full in the benchmark rather than only reporting the flattering low-concurrency figure.

Question 11

What is included in Cognocient board-ready reports?

Accepted Answer

Cognocient generates CFO-grade PDF reports in one click. Each report includes an AI-written narrative analysis of spend trends, full spend breakdown by department, team, and model, waste recovered vs. prior period, an AI Efficiency Score (cost per business outcome, trended month over month), and FOCUS-aligned export for FinOps platforms. Reports can be automatically delivered to your finance team by email each month.

Question 12

How much does Cognocient cost?

Accepted Answer

Cognocient offers three plans — Base, Growth, and Business — each with a 10-day free trial and no credit card required. Base covers real-time spend observability, Growth adds budget enforcement and waste-reduction automation, and Business adds full CFO-grade reporting and AI advisory. See cognocient.com/pricing for current plan pricing and a full feature comparison.

Question 13

Is Cognocient secure? Does it store prompt content?

Accepted Answer

Cognocient is a financial control layer, not a prompt logging tool. By default, it does not store prompt or response content — only metadata like token counts, model, feature tag, cost, and latency. Debug tracing is opt-in per feature via request header. All traffic is encrypted in transit. The platform is designed to meet enterprise security requirements.

Question 14

What happens if Cognocient's proxy goes down?

Accepted Answer

Cognocient fails open by default. If the budget-check layer becomes unreachable, API calls pass through to your AI provider unaffected — you temporarily lose cost visibility and enforcement, but your application keeps working. We prioritize your production uptime over enforcement; a Cognocient outage should never take down your AI features. Individual budgets can be configured to fail closed instead — blocking calls rather than letting them through unmetered — for workloads where that tradeoff makes more sense, such as anything touching financial transactions. See /docs/reliability for the full behavior and how to configure it per budget.

It's 7am Monday. Your AI bill doubled overnight.
You have 2 hours before your CFO asks why.

How much is recoverable in your AI bill?

Can you answer these right now?

From black box to boardroom clarity

Point your API calls at Cognocient

Every call is tagged and attributed

Waste detected. Savings surface automatically.

Everything your CFO and CTO
have been asking for

Five places your AI budget disappears

Context Bloat

Retry Waste

Model Mismatch

Cache Misses

Context Starvation

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Your AI resolves 850 tickets/month. Is it worth the cost?

5 AI features in production. One bill. Which one is spiking?

One agent ran all weekend. How much did it cost?

Chargeback by team. Board report in 15 seconds.

Board asks about AI ROI in 6 weeks. You need the answer now.

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It's 7am Monday. Your AI bill doubled overnight.You have 2 hours before your CFO asks why.