Solution Database / Operations
Surplus Stock Agent
Slow-moving stock sits unlisted because sales teams lack time, while buyers waste days chasing quotes. A single agent that handles the entire overstock lifecycle from photo to shipped order, with negotiation guardrails the seller sets once.
01The offer
For inventory and sales leads at industrial manufacturers and distributors, turn surplus inventory files, photos and emails into searchable listings, negotiated deals and fulfilled orders. Address the recurring problem: slow-moving stock sits unlisted because sales teams lack time, while buyers waste days chasing quotes. The value hypothesis is a faster, hands-off channel for overstock with fewer manual touchpoints; the pilot must establish whether buyers accept agent-led negotiations.
- For
- Inventory and sales leads at industrial manufacturers and distributors
- Takes in
- Inventory files, photos of shelves or pallets, forwarded emails with overstock lists
- Delivers
- Searchable listings, buyer responses, negotiated deals, packing slips and ERP updates
- Message
- Turn your surplus stock into a self-selling agent that lists, answers and negotiates while you sleep.
- Lead magnet
- A free demo that turns one uploaded spreadsheet into three live sample listings with extracted specs.
02How it works
- Extract SKUs, condition and specs from files and photos
- Enrich items with public catalog data
- Publish listings to chosen channels
- Answer buyer questions in plain language
- Negotiate within set margin floors
- Generate packing slips and update ERP on sale
Workflow
Upload inventory file, extract and enrich items, review auto-generated listings, publish to channels, respond to buyer inquiries, negotiate within guardrails, and confirm sale with logistics handoff. Start with inventory files, photos and emails and finish with searchable listings, negotiated deals and fulfilled orders.
AI and people
Use vision models to identify parts from photos and language models to parse spreadsheets, emails and chat. Enrichment pulls from public catalogs. Negotiation follows rule-based guardrails. A human reviews extracted data and listing accuracy before publishing, and approves any deal outside set floors.
Screens
Key screens: Inventory inbox, listing board, negotiation console. Use a central inbox for uploaded files and photos, a listing board with statuses (draft, live, negotiating, sold), and a negotiation console showing chat threads, price guardrails and margin floors. Provide a buyer-facing storefront preview. In this product, the first view is inventory inbox, followed by listing board and negotiation console.
Admin
Seller accounts, inventory access levels, listing approval states, negotiation guardrails, margin floor settings, transaction logs, audit trail for all agent actions and human overrides.
03Market gap
Alternatives buyers use today
Manual listing by sales teams, third-party liquidators, or spreadsheets and email chains. This differs by removing all manual handoffs and letting sellers set automated negotiation limits.
Where this wins
Each transaction trains the system on real buyer questions and negotiation patterns, building a proprietary dataset of industrial pricing and buyer behaviour that competitors cannot replicate quickly.
04Why now
Operations teams are adopting AI for exactly this kind of repeatable work, and the cost of language and vision models has dropped far enough that a narrow, reviewed workflow pays back quickly. The buyer already feels the problem: slow-moving stock sits unlisted because sales teams lack time, while buyers waste days chasing quotes.
05Proof & signals
Channels where buyers gather: Industry trade associations, procurement forums, LinkedIn groups for distributors, and direct outreach to mid-size manufacturers.. Metrics that prove it works: Two measurable outcomes: time from inventory upload to first buyer inquiry, and percentage of inquiries handled without human intervention..
Paid pilot
Run a 30-day paid pilot with one distributor: baseline is their current time-to-list and quote response rate. Success is at least 20 items listed and 5 buyer inquiries answered without human intervention, with a decision to expand if response time drops below 2 hours.
06Execution plan
MVP
One buyer type (mid-size distributor), one use case (email spreadsheet to storefront listings), first two modules (extraction and listing, basic Q&A), manual review of all extracted items before publishing.
First 30 days
Week 1: Build extraction pipeline for spreadsheets and photos. Week 2: Create listing board and storefront. Week 3: Add basic Q&A agent and manual review workflow. Week 4: Run a live test with one distributor and collect feedback.
After the pilot
Automate negotiation within guardrails, integrate pickup scheduling, auto-update ERP, add voice reorder for warehouse staff, and expand to multiple procurement channels after the paid pilot.
Retention
Subscription renews monthly as long as listings stay active; fulfillment fees create recurring revenue on each sale, and the system becomes the default channel for all surplus inventory.
Integrations
Start with CSV/Excel imports and email; later connect to ERP (e.g. SAP, NetSuite), shipping APIs, and procurement platforms.
07Investment and running costs
| Phase | Scope | Time | Budget |
|---|---|---|---|
| MVP | One buyer segment, one recurring use case. Manual review in the loop. | 2 days | $5,500 |
| Paid pilot | Accounts, roles, review states, audit trail and the first integration, hardened for two to three paying pilot customers. | 3 days | $5,000 |
| Full product | Self-serve onboarding, billing, monitoring and the wider integration set. | 6 days | $6,500 |
| Total | $17,000 | ||
| Running | Hosting | AI usage | Total a month |
|---|---|---|---|
| MVP and paid pilot (about 3 customers) | $30–$60 | $40–$90 | $70–$150 |
| Full product (about 50 customers) | $110–$210 | $280–$560 | $390–$770 |
Revenue model to test
Test subscription at USD 500 per month per seller, scaled by inventory volume, plus a 2% fulfillment fee per transaction after the first sale.
Cost drivers
Cloud inference for vision and language models, catalog data licensing, integration development, and support staff for manual review during pilot.
Safeguards
Limit negotiation to predefined price floors and margins, require human approval for any deal outside guardrails, restrict access to authorised sellers, log all agent actions, and must not publish items without human review or share buyer data outside the platform.
Take it further
Solution blueprint, rewritten from an earlier Nexibeo concept. Demand, pricing, build scope and integrations are working assumptions, not verified market findings. The MVP and the paid pilot exist to confirm them for your business before the larger build.