COST EFFECTIVENESS
Less rework.
More value from your AI.
Reduce the cost of producing AI output—and the time spent making that output useful. CIE brings contextual reasoning, evidence checks and governance into the workflows your organisation already uses.
REPORTED A/B BENCHMARK
24%
Lower output-token costs.
At the same price per output token, the reported comparison’s 24% reduction in output tokens translates directly into 24% lower output-token costs for that test workload.
Rounded from 24.05%. This is an output-cost comparison before CIE fees and other deployment costs, not a reduction in the entire AI bill.
The evidence behind the figure
- Without CIE
- 6,553 output tokens
- With CIE
- 4,977 output tokens
1,576 fewer output tokens across the reported test set.
Benchmark basis
The reported GPT-6 Astra versus Astra + CIE A/B summary covered 66 tests. Output-token reduction: (6,553 − 4,977) ÷ 6,553 = 24.05%.
The saving assumes an unchanged output-token price. Results vary by workload; input tokens, additional calls, hosting and CIE fees must be included when assessing total deployment cost.
THE WIDER BUSINESS VALUE
Save the work
around the answer.
Token spend is only one part of the cost of enterprise AI. Staff also spend time checking answers, reconstructing context, investigating errors and correcting the work that follows.
Less checking and correction
Evidence-linked reasoning and visible contradictions give reviewers a clearer basis for checking an answer. Better-supported outputs reduce the correction work needed before an answer can be used.
Less repeated context gathering
Preserve the relevant history and provenance of a project so teams spend less time finding records, repeating background information and rebuilding the reasoning behind previous decisions.
Earlier error control
Examine evidence, contradictions and governing conditions before an action proceeds. Catching an issue earlier reduces the amount of downstream investigation, correction and repeated work it can create.
More focused governance and review
Decision and audit receipts give teams a traceable basis for reviewing AI and agent activity. Spend less time reconstructing what happened and more time resolving the exceptions that need judgement.
These operational savings depend on the workflow and are assessed through deployment-specific measurement. They were not quantified by the output-token benchmark. Time saved releases staff capacity; cash savings arise where actual expenditure falls.
Build the business case
for your organisation.
Discuss your workloads, integration scope and CIE pricing to assess the net value of deployment.