Material cost
Systematic optimization of bills of materials and substitutes instead of one-off corrections after the period closes.
$80K–850K / year
INVO AI supports the whole bill of materials lifecycle — from component selection and unit cost optimization, through scrap factors and substitutes, to building production stages and generating production-ready work instructions.
Components · 2,140 g airframe
AI bill of materials analysis
4 optimization opportunities found
Potential unit cost
$2,150$2,000
AI workspace for bills of materials
AI works directly inside the existing bill of materials editor — components, configuration variants, scrap factors, production stages and linked ECOs. No separate tool, no parallel database.
Describe the build
"Quad interceptor, 2.1 kg, 18 min endurance"
AI drafts the bill of materials
Components + quantities
AI optimizes
Unit cost + alternatives + scrap factors
AI validates
Conformity + export-control flags + requirements
AI builds the process
Production stages + component assignment
AI drafts the instruction
Work cell + tooling + process parameters
Human approval
Design / manufacturing engineer
AI unit cost optimization
INVO analyzes the full component list, quantities, purchase prices, available substitutes and historical bills of materials to point out ways of lowering unit cost without rebuilding the bill of materials by hand.
Current bill of materials
Interceptor airframe
Unit cost: $2,150
Margin: 55.4%
AI found 3 opportunities
Airframe shell
$80 / unit
Motor set
$50 / unit
Battery pack
Check the capacity
Optimized unit cost
$2,150$2,010
Potential saving
$140 / unit
At 100 units
Potential impact $14,000
An indicative simulation of potential savings — the values are not a guaranteed result.
AI bill of materials creator
No starting from an empty table. A short description is enough to get a first, editable proposal.
Prompt
"Quad interceptor, carbon-fiber frame, 6S Li-ion pack. At least 18 min endurance. Takeoff weight under 2.2 kg."
AI picks components from the real components available in the INVO database — not from a generic component list.
Bill of materials generated by AI
Validation
Scrap factors
Instead of entering every scrap factor by hand, AI can suggest values based on the component, the layup and cure method, historical bills of materials and previously approved values in the database.
AI recommendation
Recommended scrap factor: 1.18
Based on
AI recommends — it never overwrites approved process parameters without confirmation.
Apply 1.18Component and library intelligence
AI alternatives for: Airframe shell
For every component INVO can search the available component base and rank potential substitutes by cost, conformity, export-control flags, availability, supplier, material properties and historical use.
Airframe shell — Supplier B
Same export-control flag profile
Hybrid glass/carbon shell
Heavier by 60 g · bill of materials adjustment required
Forged carbon shell
Different stiffness profile
Possible duplicates found
AI compares bill of materials names, components, quantities, conformity and process routes to point out assemblies that may already exist in the database.
You are creating
Interceptor airframe, 6S
The benefit isn't just one fewer record — AI helps keep bill of materials master data ordered and consistent.
AI production technology
AI analyzes components, quantities, process requirements and the production environment to propose the production stages needed to build the unit.
Interceptor airframe — production stages (AI proposal)
Kitting
Prepreg → cut plies to the nesting plan · Hardware → kit per serial number
Layup
Plies → lay up in the mold · vacuum bag, leak check
Cure
Carbon fiber → cure oven, cycle recommended from the configured process
Electronics prep
Flight controller + ESCs + harness
Final assembly
Mount the prepared sub-assemblies
Flight test
Acceptance flight · 2.1 kg
Packing / dispatch
Assign the configured packaging and delivery lot
AI knows at which stage each component enters
Once the stages are generated, every component is assigned to the steps where it is actually used.
The bill of materials stops being a list of components. It becomes a work instruction for building the product.
Production instructions
From the approved bill of materials and production stages, AI can prepare a draft work instruction for the production team — in the context of a specific plant.
Plant context used
Work instruction — draft
Stage 03 — Carbon fiber cure
AI uses approved process parameters, equipment specifications and plant procedures. The model's own knowledge is treated as support when preparing a proposal — never as a source of airworthiness parameters. Every instruction requires human approval.
Configuration optimization
A level above a single bill of materials: AI analyzes hundreds of bills of materials at once against material cost, conformity, component availability, waste, production capacity, purchasing requirements and margin.
An indicative simulation of potential savings — the values are not a guaranteed result.
Business impact
The effect shows up in unit cost, in the time of the engineering team and in the repeatability of production.
Material cost
Systematic optimization of bills of materials and substitutes instead of one-off corrections after the period closes.
$80K–850K / year
Design and manufacturing engineering time
The first version of a bill of materials, the scrap factors and the stages arrive as a proposal to approve.
30–50% shorter bill of materials creation
Process standardization
Production stages and instructions in one consistent format across the plant.
fewer execution variances
Master data order
Detecting duplicates and variants limits the growth of the bill of materials database.
fewer records to maintain
Indicative values for production at $14–55M revenue scale — an illustrative simulation, not a declared result.
BOM & Configuration Intelligence
Book a walkthrough: from a description of the build, through cost optimization, to a work instruction for production.