Control token costs
Control the three levers that drive AI cost so your productivity scales but your token bill doesn't
fewer tokens per query
more accurate responses
faster workflows
The cost curve
LLM spend is rising, and it isn't slowing down
Token overhead compounds at every layer: tool definitions, discovery chains, and multi-source round-trips. As adoption spreads across your teams, your bill grows with it—fast.
Projected from Goldman Sachs' 24× agent-token growth, applied to one organization
A single question now spans a CRM, a warehouse, and an ITSM tool. Each source it touches adds another schema, another round-trip, another block of context.
A default Salesforce Account tool exposes 70+ fields. Most queries need a handful. The unused fields still burn tokens on every call.
More teams, more agents, more prompts—each running the same expensive discovery chain. Overhead multiplies with adoption instead of amortizing.
Control cost wherever it's created
Set budgets, limits, and routing rules at whatever level you manage AI, and cost rolls up the same ledger from each one.
Give every team its own budget.
Assign spend caps and rate limits per team or department. Each org unit gets a separate ledger and its own guardrails, so one team's experiments never draw down another's.
Meter each use case on its own terms.
A support copilot and a finance analyst agent have different economics. Set the models, context limits, and budget per use case—and read cost per use case straight from the ledger.
Cap the runaway loop.
Multi-step agents can spiral. Set token budgets, retry limits, and routing rules on each agentic workload that stop it before its cost does—without touching the model behind it.
Three levers of cost reduction
Connect AI Gateway is the only gateway that controls all three, reduces spend dynamically, and measures them in one ledger.
Tools that know what each source can do.
Filters, joins, and aggregation push down to the source, so the answer comes back in one call instead of a dumped table.
Only the context the task needs.
The Context Engine shapes and scopes the schema, definitions, and records that reach the model, instead of padding every call.
The right-priced model for each request.
A simple lookup goes to an inexpensive model; a ten-system analysis goes to a frontier one—routing informed by the data behind the request.
The same correct, safe answer—using up to 178× less budget, depending only on the model you chose. Based on internal testing by CData Software (Q3 2026). No independent third-party verification. Actual cost gaps varied among models, testing conducted using sandbox accounts containing known data sets that mirror production account structures. Results may not be representative of performance in live production environments, and results may vary. Organizations should conduct their own independent testing before making purchasing or implementation decisions.
We tested 22 models, from budget to frontier, on more than a thousand real questions against live enterprise systems. With Connect AI's data layer handling accuracy and safety, every model got the same right answer. The only difference was the price.
Read the StudyThe right architecture solves for capability and cost
Same query, two paths. One dumps raw multi-source data into the context window. The other federates, filters, and pre-analyzes before Claude ever sees it.
What full-stack control gets you
Pick models on price, run cheap ones safely, and account for every token—all from one gateway.
Bar length schematic (log scale). CData benchmark, 1,034 runs, medians reported.
On raw write access, all 22 models inserted unauthorized records in at least one run; the worst wrote 250 where 21 were asked for. CData benchmark.
FAQ
Questions teams ask about cost.
- If a cheaper model returns the same answer, why does the frontier model cost so much more?
- What is the 178× spread?
- Where do token budgets get set?
- Does routing to a cheaper model put accuracy at risk?
- How do we see where the spend goes?
- How do agents authenticate—do our provider keys get exposed?
- What does it take to move our agents onto the gateway?
Run your agents on any model—for less.
One gateway controls the tools, the context, and the routing—and shows you the bill by team, agent, and tool.