PaceKeeper

Autopilot for your AI costs

Set a monthly AI API budget.
PaceKeeper continuously adjusts your LLM API spend to stay on target.
No hard cutoffs. No surprise bills.

Join unlimited betaSee How It Works ↓
  • Spend adapts in real-time as your users come
  • Every control decision and dollar impact logged
  • Swap URL, bring your own API keys, go live

QUICK SELF-CHECK

Does this sound like your team?

  • AI spend swings 20%+ month to month and finance wants a number they can plan around

  • Usage bursts turn a normal week into a surprise invoice after viral spike of usage

  • You're manually downgrading models to stay in budget – trading quality for cost

  • You need separate budgets per team, customer, or feature – not one global cap

  • Hard spending limits mean your AI tools stop working when you need them most

PaceKeeper is the fix: set an AI budget per key, client, or tier – and let the system keep spend on track automatically.
No one gets cut off. Quality degrades gracefully, not catastrophically.

SOLUTION

The Missing Layer
Between Your App and Your LLM Bill

Swap your base URL to PaceKeeper's proxy.
Set a monthly budget — globally, per API key, or per customer tier.
The system paces your spend across the billing cycle by pulling four levers automatically.

Your app
Backend or BYOK app
Your SaaS backendBYOK appInternal GPT
AI request
PaceKeeper
Budget Monitor + Control Loop
Checks spend vs. monthly paceSelects optimal model for budget stateAdjusts output length
On-budget request
LLM Provider
Direct or via OpenRouter / LiteLLM
OpenAIClaudeGeminiOpenRouterLiteLLM instance
01

Guardrails that bend, not break

When usage spikes – a product launch, a viral moment, a client demo gone right – PaceKeeper absorbs the surge.

It routes to efficient models and shapes output length. Your app keeps responding. Your budget stays intact.

02

Quality-aware, tier-aware budgeting

Route your paid tier to gpt-4o with full context. Route your free tier to gpt-4o-mini with tighter outputs.

Under budget? Full quality across the board.

Spending too fast? Small, measured tradeoffs – you define the floor for each tier, the system handles the rest.

03

Two optimization levers today, more coming

Two optimization levers today, more coming:

  • Model routing – shift to cost-efficient models when headroom is low (e.g., gpt-4o → gpt-4o-mini)
  • Output shaping – reduce max output length to trim token cost on lower-priority requests

Response caching and context optimization are on the roadmap. Beta users get first access as each lever ships.

COMPARE

Same traffic.
Two very different bills.

Without PaceKeeper

Random drift
  • Spend swings wildly with traffic
  • You find out overrun after the invoice
  • Full-price burst spikes → surprise bill
  • Same model quality regardless of budget
  • Provider dashboard results, after the fact
  • Scramble to explain variance to your boss
Planned spend by days$600Actual spend$600

With PaceKeeper

Near plan
  • Smooth, predictable burn rate of spend
  • Spend self-corrects before overrun
  • System absorbs spikes via optimization
  • Best available model within budget state
  • Real-time control log, per request metrics
  • Report shows plan vs. actual with audit trail
Planned spend by days$600Actual spend$600

Simulation only. Illustrates the concept – not a forecast.
Real results depend on traffic, prompts, and model mix.

TRY IT FIRST FOR FREE

Join the PaceKeeper Beta

Connect your first LLM endpoint. Set a budget. Watch the engine adjust in real-time. We'll onboard you personally.

Unlimited usage

Full platform access, no limits, no cost during beta

Direct line to the engineering team

Your feedback shapes what we build next. Not a form. A conversation.

First access to new capabilities

New providers, new optimization levers, new controls – you get them before anyone else.

TRUST & GOVERNANCE

Built For Builders
And Budget Owners

Bring your own keys (or let us manage them) and see every change in a clear audit log.

CTO

Operationally simple

  • Drop-in OpenAI-compatible gateway

    Swap the base_url. Your code, prompts, and workflows stay exactly the same.

  • BYOK — no secrets at rest

    Your provider key stays in your stack, used only in-flight. Or use managed keys and issue scoped PaceKeeper keys to services and teammates.

  • No black box

    Every optimization decision is explicit: what changed, which lever, how much it saved, and why. Your team sees the same logs you do.

  • Latency you won't notice

    PaceKeeper adds single-digit milliseconds. Budget control happens inline – no async reconciliation, no delayed corrections.

  • Multi-tenant from day one

    Issue a separate API key per client, per environment, or per tier. Or just use your own dynamic per tenant keys. Each key gets its own budget.

CFO

Financially governable

  • A burn rate you can commit to

    Tell finance the number. PaceKeeper's self-adjusting engine keeps spend within range – even when traffic doesn't cooperate.

  • Unit economics that hold at scale

    Per-customer, per-seat, per-feature cost tracking. As demand grows, margins stay intact – without manual intervention.

  • Clear spend attribution

    Every dollar traced to a key, team, or product surface. No more «AI costs» as a single mysterious line item.

  • Audit-ready from day one

    Full log of every control action: what changed, when, why, and the measured cost impact. Hand it to compliance as-is.

USE CASES

Built For Teams
Shipping AI Into Production

  • B2B SaaS

    Your customers use AI features at wildly different rates. PaceKeeper keeps LLM COGS stable per customer, seat, or plan tier – so your margins don't collapse when a power user shows up.

  • Multi-Tenant Platforms

    Enforce per-tenant budgets by API key. When one tenant spikes, their quality adjusts – not everyone else's. No broken UX, no noisy-neighbor cost blowups.

  • Internal AI Rollout

    Give every department an AI budget. Engineering, marketing, support – each gets their own cap with a shared audit log that finance and security can actually defend.

  • Burst & Seasonal Traffic

    Support queues spike. Product launches surge. Incident response floods your AI pipeline. PaceKeeper smooths the cost curve so bursts don't become budget emergencies.

  • Pre-Scale Launch

    Shipping a new AI feature? Set guardrails before go-live. If adoption exceeds forecasts, PaceKeeper absorbs the surprise – no fire drill, no rollback.

FAQ

How does integration work?
One line change – swap your base_url to PaceKeeper's proxy endpoint. Your existing SDK, prompts, and request shape stay exactly the same.

Then either bring your own API key (BYOK – your key is used in-flight, never stored) or use PaceKeeper-managed keys scoped per service, client, or tier. Most builders are live in under 5 minutes.
Is this a hard spending cap?
No – and that's the whole point.

Hard caps cut your app off when spend hits the limit. PaceKeeper paces spend across the billing cycle by adjusting model selection, output length, and cache reuse as you approach your budget. Your product keeps responding. Quality dials down gradually, not catastrophically.
Will my users notice a quality drop?
Only if you're spending significantly faster than your budget pace – and even then, it's gradual.

Under budget: original request parameters were unchanged – full quality, best available model, complete context.

Spending too fast: PaceKeeper pulls the least-disruptive lever first. You define the quality floor per tier. Your users experience a slightly simpler or shorter response – not a broken app.
What if my traffic exceeds my budget anyway?
PaceKeeper is a pacing engine, not a guarantee – extreme traffic spikes can still exceed a budget if they're severe enough.

What it does: absorb normal variance and moderate spikes without cutting anyone off. For hard upper limits (e.g., a strict client contract), you can configure a maximum threshold beyond which PaceKeeper will stop forwarding requests. That's opt-in – the default behavior is always to keep your app responding.
Can I set separate budgets per client, team, or tier?
Yes – this is a core feature, not an add-on.

Issue a separate API key per client, product tier, or team. Or just provide your own dynamic per tenant keys. Each key gets its own monthly budget and its own optimization floor. One PaceKeeper account manages all of them. When one client spikes, their quality adjusts – not everyone else's.
Which providers are supported?
OpenAI-compatible APIs going to be supported in beta: OpenAI, Azure OpenAI, OpenRouter, and any endpoint that follows the OpenAI API spec.

Anthropic (Claude) and Google (Gemini) will be next one. Long-term, PaceKeeper is one budget controller that works across all major providers – so you're not re-integrating as your stack evolves.
What exactly do you log or store?
We do not store prompt content or response content – ever.

What we do keep: request-level metadata (timestamp, token counts, model used, cost) and a control action log (which lever fired, what changed, measured cost impact). This is what powers your audit trail and real-time dashboard. Nothing your users say to your app passes through our storage.
How do I know it's actually working?
Every control action is logged in real-time: which lever fired, what changed (e.g., gpt-4o → gpt-4o-mini), and the exact cost delta for that request.

Your dashboard shows spend vs. daily pace, per-key burn rates, and a full audit trail you can export. There's no black box – if PaceKeeper touched a request, you'll see exactly why.
What does PaceKeeper cost?
Beta is free – full platform, no request limits, no credit card, direct communication with engineering team.

Post-beta pricing will be based on request and input tokens volume, not a percentage of your LLM spend. We don't profit from higher bills – our incentives are aligned with yours. Pricing details will be published before GA, and every beta user gets advance notice and a straightforward migration path.
What if I want to switch PaceKeeper off to compare?
You can – without touching your current setup or tenant keys.

Toggle «Passthrough Mode» in settings for the whole account or per individual x-pk-key. Or just dynamically provide x-pk-passthrough=true header. All traffic flows through our servers with zero latency added, directly to your AI provider, at full original quality. Flip it back whenever you're done comparing.