Cut AI costs.
Increase profit on every customer.
ensemble gives every agent only the business knowledge it needs for the task — reducing token usage, AI COGS and cost per completed result. Fewer tokens in. Lower AI COGS. Higher gross margin.
Same decisions. Fewer tokens.
ILLUSTRATIVE EXAMPLE — YOUR BASELINE IS MEASURED ON YOUR OWN WORKLOAD BEFORE ANY TARGET IS AGREED.
| Benchmark | Result |
|---|---|
| Caching alone | 83% cost reduction demonstrated in a small agent workflow |
| Caching + input trimming | 88% cost reduction demonstrated |
| Optimized multi-turn agentic workloads | 45–80% API cost reduction reported |
BENCHMARKS ARE THIRD-PARTY / PROVIDER RESULTS AND DO NOT REPRESENT GUARANTEED ENSEMBLE SAVINGS — ACTUAL SAVINGS DEPEND ON ARCHITECTURE, MODELS, PROMPTS AND WORKLOADS.
Knowledge routed per task, not per prompt.
Shared business-knowledge layer
Task-scoped context routing eliminates repeated knowledge transmission across agent chains.
Agent-specific context routing
Each agent receives only what is relevant to its step — unnecessary token consumption disappears.
Usage analytics & cost monitoring
Token analysis, context-duplication detection and per-task cost breakdowns — you see where the money goes.
Built for products where AI usage is COGS.
The more often your agents repeatedly process customer-specific business knowledge, the larger the optimization opportunity.
Multiple agents repeatedly consume the same brand, market, ICP and product knowledge. ensemble provides task-specific business knowledge to each stage. Result: lower cost per generated asset.
Agents repeatedly analyze companies, markets, competitors and previous findings. ensemble makes validated knowledge reusable across future tasks. Result: lower research cost per customer.
Prospect research, company knowledge, positioning and previous conversations are repeatedly processed. ensemble routes only relevant knowledge into each action. Result: lower cost per qualified action.
Product rules, customer history and support knowledge create large recurring context. ensemble provides the relevant subset for each request. Result: lower cost per resolved request.
Without structured shared knowledge, information gets repeatedly passed through agent chains. ensemble creates a shared business-logic layer between them. Result: lower cost per completed workflow.
Large internal AI systems repeatedly consume company processes, policies and operational knowledge. Result: lower enterprise inference spend.
28 PRODUCT SHAPES ARE COVERED IN THE CATALOGUE — RECRUITING, LEGAL, FINANCIAL, CLINICAL, LOGISTICS AND MORE.
Audit first.
Audit
- Token analysis and cost breakdown
- Optimization opportunity assessment
Your agents are overpaying for context.
A free audit shows how much — on your own workload, before you commit to anything.