01
The Tiers
Priced on conversation volume, the model you run and whether your infrastructure is shared or dedicated. Monthly is all-inclusive: Azure consumption, framework licence and support. Figures in USD.
Dedicated infrastructure starts at Professional. Below that, your environment is isolated within a shared Azure footprint, which is what makes a pilot inexpensive enough to be worth running before you commit.
02
What the setup fee buys
Itemised, because a single implementation number tells you nothing about what you are getting. Most deployments need little custom development, the work is Azure configuration, loading your knowledge and training intent.
Two shapes sit behind these numbers. Full is production grade, intent classification, entity extraction, hierarchical search, contextual imagery and stands up in one to two weeks. Lite is a proof of concept on Azure AI Search alone, retrieval without intent classification and no complex indexing: one to two days. Lite is the honest shape for a pilot.
One thing to plan for. Answer quality tracks the knowledge-base line above, not the tier you buy. Curating what the assistant is grounded in is the work that decides whether it is useful, so it is priced as work, not bundled out of sight.
03
What it costs over time
Year one carries the setup fee. Year two onward is monthly only.
At 100,000 conversations a month
Three-year totals, and what each figure includes
Ours includes setup, framework licence, Azure infrastructure and support. The competitor figures are platform fees only, they exclude implementation, custom development and, where applicable, the cloud infrastructure and model usage billed separately. Read section 05 before the table.
At 500 users the gap is structural, not efficiency. Copilot Studio’s three-year total of $3.7M against our $532K–1.05M is a per-user licence at $200 a month, multiplied by headcount. At 50 users the two are level; the difference is what happens as your organisation grows.
Three-year total at 100,000 conversations per month
Bars proportional to the largest total. Ours shows its floor solid and its ceiling pale.
BWA Agent Accelerator
$532K – $1.05M
Copilot Studio (500 users)
$3.7M
Solid = our floorPale = our ceilingSteel = platform fee only
04
What each platform bills you for
The unit matters more than the rate, because it decides what makes your bill grow. Each vendor’s own published figures.
Per-user pricing grows with headcount, so you pay for people who never open it. Per-request pricing grows with every turn of every conversation, and bills the model separately. Ours grows with volume, in one line, and you can see the Azure inside it.
05
Scope, and how to read the comparison
The part most pricing pages leave out.
01
What the monthly covers
Azure consumption, the framework licence and support, one line, all-inclusive, with no per-seat component.
02
What is separate
Setup is a fixed one-time project fee, quoted from the table above. Engineering work beyond it, new integrations, custom development is hourly or on retainer.
03
How the comparison is built
Our figures include setup, licence, Azure infrastructure and support. The competitor figures are platform fees only: they exclude implementation, custom development and, where applicable, the cloud infrastructure and model usage those platforms bill separately.
04
On the comparison table
On platform fees alone, Google and AWS come in below our floor. We show that rather than omit it their line is a platform fee, ours is a delivered system, and the two are only comparable once implementation is priced in.
06
You can take the infrastructure with you
It is built entirely on Azure, so all of it can move to your own subscription at any time. None of the alternatives above can offer that their platform is the product, so leaving it means rebuilding.
Why it costs what it costs
01
No per-seat licensing
Costs stay consumption-shaped and predictable. Adding people to your organisation does not add to the bill.
02
Less to build
The pre-built framework saves an estimated 60–80% of development effort and reaches production sooner.
03
Lower maintenance overhead
Standard Azure services throughout. No proprietary platform expertise required to keep it running.
04
Model flexibility
Swap AI models as better ones appear, with no migration cost for component upgrades.