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Lorikeet Overview for TerraPay

A team of AI agents that resolves partner status queries end-to-end, across 500 partners, every corridor, every channel.

Prepared for Ashok Gajarajan, Rupee, Kameshwar & Ashirbad · 15 May 2026
Robbie Tilleard, Lorikeet

The Opportunity

Resolve the 30k monthly "where is my money" queries automatically, in the partner's channel of choice. Free the 100-person ops team for the work that actually needs human judgment.

Resolved, not deflected

Partners get a real answer the first time, with corridor rules, payout-partner state and SLA all factored in. No more "let me check and get back to you" while a sender waits on Taptap Send waits on you.

Always-on, every channel

Email, Slack, WhatsApp, Teams, social — partners hit you wherever they want. Lorikeet replies in the channel the query came in on, 24/7 across every corridor and timezone.

Real efficiency

No more bouncing between five ops screens for a single status query. The agent diagnoses delay reasons, re-pushes failed transactions, and chases POD — in seconds, not minutes.

Redeployed ops

100 people stop being the manual middle layer between partner inboxes and your DBs. They focus on partner success, network growth, and the exceptions only humans can resolve.

State of Play at TerraPay

~30,000 status queries per month across ~500 partners globally — from Taptap Send in the UK to partners in Tokyo, Melbourne, Colombia, Chile, Peru. Handled by a 100-person ops team.
Every query is multi-screen — ops queries the DB by transaction ID, massages binary/alphanumeric responses, summarises across compliance / payout / tech systems, then replies in whatever channel the partner used.
Channel fragmentation — partners reach you on Slack, WhatsApp, email, Teams, social. Reply has to land in the same channel the query came in on. Today that's manual copy-paste.

Three things the agent has to get right:

Corridor intelligence — Pakistan is real-time, Bangladesh has cutoff times and Fri/Sat banking holidays, India has IMPS + NEFT rails. The agent picks the right rule before it answers.
Operational work, not just answers — re-push failed IMPS via NEFT, chase POD from payout partners, initiate reversals on wrong-beneficiary cases. Tools, not just text.
Team of agents, not one agent — one specialist talks to the partner, another chases down transaction state, a third coordinates the POD request. Orchestration is the unlock.

Three scenarios, three capabilities

Built as a working sandbox — synthetic transaction data, real workflows, real agent. Try them live on the next slide.

01

"Where is my £100 to Vietnam?"

Taptap Send asks about a delayed real-time corridor transfer. Agent looks up the txn, reads the corridor rules, checks the payout partner's network status, identifies a partner-side stall, and quotes a real ETA — not "let me check."

Corridor intelligence + multi-tool diagnosis. The 30k-a-month query type.

02

"IMPS failed to India — push it through?"

Agent diagnoses the rail failure, proposes the NEFT alternative with realistic SLA, and executes the reroute. Policy guardrail prevents auto-confirming a delivery time without a corridor lookup.

Write action with safety rails. Agents that do ops work, not just answer questions.

03

"Customer says they didn't receive it"

Non-credit complaint on a success-flagged transfer. One agent checks the POD API. POD isn't available in this corridor, so a second agent fires off a POD request to the payout partner, then updates Taptap Send that POD is being chased.

Team of agents. One talks to the partner, another chases the partner of the partner.

Also handled in the same sandbox (happy to dive into any): cutoff-corridor queries (Bangladesh banking holidays), pure delay diagnosis (compliance vs payout vs tech vs insufficient funds), wrong-beneficiary reversals.

Try a ticket against the live agent.

Mock partner-portal UI on the right, with the real Lorikeet chat widget embedded against a TerraPay sandbox. Synthetic transactions, real agent, real tools. Start any conversation by saying "I'm Taptap Send Ops" so the agent knows which partner you are.

Try: Vietnam status query

I'm Taptap Send Ops. One of our senders is asking about transaction TPV-4471 to Vietnam — £100 sent yesterday afternoon, not yet received. Where is it?

Try: IMPS reroute

I'm Taptap Send Ops. Transaction TPV-5582 to India failed via IMPS. Can you push it through on NEFT?

Try: non-credit complaint

I'm Taptap Send Ops. Transaction TPV-6603 to Kenya was marked successful three days ago, but the customer says the funds never arrived. Can you confirm proof of delivery?

Answers cite synthetic transaction state plus your real corridor rules and POD process. Wrong-beneficiary reversals and cutoff-corridor queries run on the same sandbox — happy to demo on request.

Appendix

Lorikeet overview, the team, investors, customer voice, architecture, POC plan, security, and pricing.

Lorikeet is building the leading AI concierge for complex businesses

Lorikeet exists to give every company the ability to deliver a universal concierge to their customers. Customers should demand better support, Lorikeet's platform solves issues by understanding customer needs and taking actions for them, 24/7, via the channel of their choice.

Re: Status of TPV-4471, Vietnam transfer for Anjali S.

Lorikeet

To: Taptap Send Ops

Hi team, TPV-4471 is currently held at our Vietnam payout partner — their domestic switch is reporting intermittent timeouts since 08:14 UTC. Funds are safe.

Per the VN real-time corridor SLA, expect delivery once the switch clears (typically <2h). I'll send a follow-up the moment we see the credit confirmation.

Email

Lorikeet

0:08

"Hi, this is TerraPay's partner concierge. I'm calling about transaction TPV-5582 — the IMPS attempt failed at 09:42 IST. Want me to re-push via NEFT? Delivery in two to three hours."

Voice

Status of TPV-6603 to Kenya? Customer says they didn't receive it.

T

Marked delivered 3 days ago, but no API-side POD for Kenya. I've requested POD from the payout partner now.

How long for confirmation?

T

Partner SLA is 24h. I'll send the POD straight back to you here once it lands.

Chat

Our people have decades of experience with AI and building great products

CEO and Co-founder

Steve led product teams at Stripe and Watershed, building tooling to enable complex processes like carbon accounting and financial reporting at scale.

CTO and Co-founder

Jamie was a research tech lead at Google Brain, leading research on factual grounding in large language models. Third named author on Google's breakthrough 2022 LaMDA paper, and fourth named author on the 2020 predecessor Meena paper.

Our team comes from leading companies applying AI and driving large-scale corporate transformation

Lorikeet is backed by top global investors

We've raised over $50M from investors who backed Nubank, Klarna, Canva, Airwallex, Supabase, Midas, Clearscore and more.

Announcing our

$35M

Series A

Led by QED Investors

Blackbird

Square Peg

Capital49

Skip Capital

Airtree

Operator Partners

www.lorikeetcx.ai

Lorikeet consistently outperforms other vendors in the market

"We tested AI solutions head-to-head and Lorikeet was a winner in every metric."

Lindsay Boland

Product Manager, Flex

"We ran POCs with Fin AI, Decagon... Lorikeet was a clear winner."

Jiaona Zhang

Former CPO, Linktree

"Considered Sierra and other well-known players... [Lorikeet] could handle nuance, de-escalate emotional moments, and follow SOPs without breaking a sweat."

Jessica Mishlove

Head of Customer Relations, Arbor

Read case studies

Already automating partner support for cross-border payments leaders

Journey of a Support Ticket

How Lorikeet's AI agent resolves customer issues end-to-end

1

Customer sends message

Via chat widget, email, WhatsApp, voice, or ticketing system

2

Channel Intake

Mode (chat / email / voice / SMS) · Escalation rules · Auto-close config

3

Brand + Config Loaded

TerraPay voice · Partner-facing tone · Per-corridor rule set

4

Inbound Guardrail

Evaluate message → pass to triage, or escalate immediately

5

Intent Classification

AI matches customer intent against all available workflows

Matched Workflow

Run response SOP

FAQ Fallback

Search knowledge base

No Match

Escalate to human

6

Workflow Executes

Structured decision graph or Natural Language agent follows step-by-step SOP

Tools

Txn DB · Corridor rules · Partner status

Knowledge

POD process · Reversal policy · SOPs

Actions

Reroute · POD chase · Tags · Notify partner

7

Outbound Guardrail

Check AI response against policies → pass or escalate

8

Reply Sent to Customer

Brand voice · Formatting · Citations · Side effects (tags, CSAT, Slack)

If customer replies → loops back to step 5 with full context

If no reply → auto-resolved after idle period

Proof of concept

2–4 weeks, offline, free, to prove Lorikeet handles real TerraPay partner status queries end-to-end across the 2–3 highest-volume corridors
We'll mock the partner data to simulate production situations, rather than integrate with your platform on day one
Zero risk, if it doesn't meet the bar Rupee's team sets, no obligation to proceed
Live pilot with one partner, e.g. Taptap Send for the UK–Asia corridors, then scale by partner cohort once we're hitting the resolution rate you want

Train and test AI

Integration scoping

Legal / privacy / security review

Week 0–1

We will:

Train Lorikeet's tone and brand from your guidelines
Run response testing over 20–50 example tickets
Plan training based on your SOPs

We need:

Tone of voice, SOP, ticket corpus
Fast feedback on tickets

Week 1–2

We will:

Build, test and iterate on 1–2 agreed use cases
Share learning materials with your team
Produce documentation to aid implementation

We need:

Continued feedback on AI response quality

Week 2–3

We will:

Run Lorikeet 101 training session with your champion
Complete any necessary security and legal reviews
Agree on terms of contract including cost

We need:

Tech lead to align on integration plan

Week 3–4

We will:

Complete security and legal reviews
Kick off integration sync

We need:

Agree on commercial terms and sign

Lorikeet is built securely for enterprise

Compliance-grade architecture, day one. Designed for FCA-regulated fintechs and cross-border payments infrastructure handling sender PII and transaction data.

SOC 2 Type II
& ISO 27001

Both certifications independently audited. Your data is always protected and is never used for training.

GCP + VPC

Built on Google Cloud, running in a virtual private cloud. Audit-grade logging end-to-end.

Ex-Stripe security

Founding engineering team includes an ex-Stripe Staff Security Engineer. Security reviewed by industry leaders.

Handles sensitive PII at scale

Already deployed with FCA-regulated cross-border payments players (Airwallex, Taptap Send) handling sender PII, transaction data, and partner-level commercial info at scale.

For TerraPay's data posture: sender PII, transaction IDs, partner-level commercial data, and compliance hold internals all need strict handling and audit trails. We're happy to walk your security and compliance leads through our controls, data residency by region (US / EU / AU), access controls, and incident response.

View trust center →

You only pay for resolutions

Aligned incentives by design, we both win when tickets are resolved.

Pay only for resolved tickets

Lorikeet charges per ticket successfully resolved, as determined by you. If we don't deliver, you don't pay.

No platform or per-seat fees

No setup costs, no per-seat licenses, no monthly minimums. The only line item is resolutions.

Volume discounts

Per-resolution price decreases as volume grows. Available across email, chat, voice, and SMS.

Aligned incentive structure

You buy credits from Lorikeet up front
Credits are only consumed when the AI reaches the desired outcome
You don't pay if the AI fails and the case is passed to a human
Credits sized to your forecast volume, buy top-up packs at a discount mid-contract, no surprise overages

At TerraPay's volume: ~30,000 status queries / month puts you firmly in our enterprise tier. Exact per-resolution price depends on the workflows we scope during the pilot, with volume-based step-downs as more corridors come online. We'll model the breakeven against the 100-person ops team during the next session.

Robbie Tilleard

robbie@lorikeetcx.ai