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Token Use Calculator

Use the inputs below to estimate the number of AI Actions your team will take, to see how much you will save when switching from a RAG-based system to the Enterprise Intelligence Engine. You can adjust the estimated number of tokens per query and token price in the assumptions section.

Your organization

People who access the knowledge base.

100 500 2,000 10,000

Searches plus agentic actions, per user.

1 3 5 10

Total documents in your ecosystem.

1,000 10,000 100,000 1,000,000

What the context tax costs you in consumption charges:

—fewer tokens per query

—
AI Actions per month, all users
—
times more efficient per query
—
saved per year, all users
—
saved per query, on average

Token usage per month, all users

Traditional RAG

—

tokens per month

— tokens / query

Bloomfire EIE

—

tokens per month

— tokens / query

Documents considered per query

Traditional RAG

—

of ecosystem considered

— documents referenced per query

Bloomfire EIE

100%

of ecosystem considered

— documents referenced per query

Adjust the assumptions

Traditional RAG

Full context, retrieval, and answer, combined

$ per 1M tokens, blended input/output

Fixed retrieval window — doesn’t grow with the ecosystem

Bloomfire EIE

Context drawn from persistent memory, plus answer

Years in your Bloomfire contract

This is a directional model, not a certified benchmark. RAG cost is modeled as users × queries and actions per day × tokens per query, priced at a blended rate per token. EIE cost is modeled as documents ingested × cost per document, amortized across the contract length and expressed as an annual figure — it does not scale with query volume, since the expensive understanding happens once at ingest rather than on every search. Documents considered per query reflects RAG’s fixed retrieval window (a constant, editable top-k that does not grow with the ecosystem) against EIE’s persistent semantic memory, which reasons over the entire ecosystem regardless of its size. Monthly figures assume 21 working days per month, and annual figures assume 252 working days per year (12 × 21), the days your team is actively using AI. Edit any assumption above to match your own measured numbers or contract terms.

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Connect knowledge pools of documents, conversations, media, data, and expertise with your Persistent Semantic Memory™ to ground your AI. Use our turn-key of connectors or build your own to connect to any enterprise systems.

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