RESOLVECHAIN Investor Pitch · v0.1 · 2026
AI-agent call centers · paid on results, proven on-chain

The $380B call-center bill,
rebuilt on proof

ResolveChain runs the full ticket lifecycle with AI agents, records every action immutably on-chain, and pays per resolved ticket — replacing the opaque per-headcount model that makes SLA disputes routine.

Choose a chapter · arrow keys to navigate
Problem & market
Product
Business & moat
01 · Positioning

Billed per headcount vs. paid per resolution

The same outsourced customer-service work, reframed: from an opaque contract that invites disputes to a settlement layer where results are measured and proven.

Today · per-FTE outsourcing
Pay per seat → trust the vendor's numbers → reconcile by hand → dispute the SLA
Cost scales with headcount, not outcomes — and neither side can prove what happened.
ResolveChain · pay-per-resolution
AI agent resolves the ticket → action & CSAT hashed on-chain → smart contract pays per resolved ticket → auto-compensates on breach
Cost scales with results, and the record is immutable — disputes disappear.

"The $380B call-center industry still bills like it's 2005. We turn service into a metered, provable outcome."

02 · The problem

A huge market billed on seats, not outcomes

Call-center outsourcing still charges per full-time employee — an outdated model with no shared, verifiable record of performance, so SLA disputes are routine.

$B
Outsourced customer-service spend — still billed per FTE
Per-FTE
You pay for seats occupied, not tickets resolved
Manual
SLA reconciliation done by spreadsheet, after the fact
Both sides
Each party controls its own numbers — disputes are routine

"There is no common standard for transparency, measurement, or payment. That gap is exactly what ResolveChain fills."

03 · Solution — four pillars

AI agents do the work; the chain keeps them honest

AI handles the entire ticket lifecycle while the blockchain acts as a transparent, immutable recording and payment layer.

Pillar 01

AI agent orchestration

Handles receive → classify → resolve → escalate end-to-end, learning from each client's history to raise auto-resolution over time.

Pillar 02

On-chain audit trail

Every action, response time and CSAT result is hashed and recorded — evidence neither vendor nor customer can alter.

Pillar 03

Pay-per-resolution

Smart contracts charge per successfully resolved ticket, and auto-compensate the client when an SLA is breached — no manual reconciliation.

Pillar 04

Portable credibility

Agents build a cross-client on-chain "credit score," so new customers can trust them from day one without a long testing period.

04 · Platform architecture

Every channel and every rule converges on one core

Enterprise customers & channels
Ticket sources: chat · email · voice · in-app support
ResolveChain core
AI orchestrationTicket lifecycle Per-client learningAuto-resolution
Blockchain ledger
Immutable audit trail of every action & CSAT
Smart contracts
Pay-per-resolution & auto-compensation
SLA / CSAT engine
Industry-specific response & quality rules
Settled outcomes
Resolved tickets · provable SLAs · automatic compensation on breach
How it fits together

Tickets arrive from every channel into the ResolveChain core, where AI agents run the full lifecycle. The blockchain ledger, smart contracts and SLA engine settle each ticket into a provable, automatically-paid outcome.

05 · Ticket lifecycle

One ticket, receive to settlement

The AI agent runs the whole lifecycle; the moment it resolves, the outcome is written to the chain and settled by contract — the two steps that make performance provable and payment automatic.

1Receive — ticket enters from any channel
2Classify — AI routes & prioritises by intent
3Resolve — AI agent handles end-to-end
4Escalate — hand to a human only when needed
5Hash on-chain — action, time & CSAT recorded
6Auto-settle — pay per resolution / compensate on breach
06 · Market opportunity

A big market already in motion

The shift to "AI agent as a service" is happening now — and economics, not novelty, are driving it.

$15.12B
AI customer-service market in 2026
25.8%
CAGR of the AI CX market
$B
Gartner: contact-center labor cost cut in 2026
$0.40
AI voice cost per call — vs. $7–12 for a human
Segment2026 outlook
AI customer-service market$15.12B · CAGR 25.8%
AI call centers$4.89B
Human agents replaced by AI20–30% (Gartner)
Cost per call (human → AI voice)$7–12 → ~$0.40
Outsourcing shifting to "AI agent as a service"$380B — no transparency, measurement or payment standard yet
07 · Business model

We earn only when the work is proven

How a ticket settles
AI agent resolves the ticket
Outcome, response time & CSAT hashed on-chain
Smart contract releases payment — per resolution
Three revenue streams
1Fee per resolved ticket — priced on outcomes, not FTEs
2Platform fee per smart-contract transaction
3Compliance & audit packages for regulated industries — finance, insurance, healthcare
08 · Competitive moat

Three moats that compound over time

Data network effect

Cross-client operational data

Every ticket across every client makes the AI more accurate — an advantage that widens with each new customer and is hard for a newcomer to match.

On-chain reputation

A track record that can't be faked

Each agent's immutable performance history is a portable asset that can't be quickly replicated — new competitors start from zero credibility.

Technical barrier

Industry-specific SLA engines

Purpose-built response and quality rules for regulated verticals raise the bar for anyone entering later.

"More clients → more data → better agents → stronger on-chain reputation → more clients. The flywheel gets harder to catch the longer we run."

09 · Why now vs. alternatives

The budget already exists — we don't have to create it

Against our other two concepts, ResolveChain sells into a cost line enterprises are actively cutting today.

AegisRail & TitanGrid
Agency commerce · AI compute — promising, but each must create or capture new budget.
Higher market risk and a longer path to the first paying customer.
ResolveChain — why now
Enterprises are cutting BPO cost right now. An established budget line, lower market risk, and a faster route to early paying customers.
We ride a shift that's already underway rather than betting on a new one.
10 · Roadmap

Land, prove, then compound

A phase opens only when the gate before it is passed.

Phase 1
Months 0–6 · Design partners
  • Onboard 2–3 enterprise design partners in one regulated vertical.
  • Ship the AI orchestration + on-chain audit-trail MVP.
Gate 1→2 · tickets resolved & settled on-chain with a design partner
Phase 2
Months 6–12 · Paid pilots
  • Convert partners to pay-per-resolution contracts.
  • Launch smart-contract settlement + SLA auto-compensation.
Gate 2→3 · recurring revenue from ≥3 paying enterprises
Phase 3
Months 12–24 · Scale & reputation
  • Expand across verticals; portable agent credit score live.
  • Ship enterprise compliance & audit packages.
Milestone · multi-vertical footprint & a measurable data flywheel

Draft go-to-market shown for discussion — real milestones, dates and gate metrics to be confirmed by the founder.

11 · The ask

Join us in metering the $380B service economy

We're raising to prove pay-per-resolution with enterprise design partners in one regulated vertical, and to ship the on-chain settlement layer that makes it work.

The ask
Stage — to confirm · Raise amount — to confirm · ~18-month runway — to confirm
Use of funds — draft
1Platform — AI orchestration & on-chain settlement engine
2Go-to-market — land 2–3 enterprise design partners
3Compliance — audit packages for regulated buyers
4Team — key AI & protocol hires

"AI is already taking over the contact center. ResolveChain makes that shift measurable, provable and fairly paid — and owns the standard for how it settles."

Stage, raise amount, runway and the use-of-funds split are to be confirmed by the founder before this deck goes to investors.