Every conversation,
resolved.
Replace your BPO with AI agents trained on your product, tone, and brand context. Trilingual ES/PT/EN from day one. Setup in 2 weeks, not 6 months.
The AI-native support layer for mid-market
Traditional support doesn't scale. Neither do the enterprise players.
Mid-market is stuck: BPOs are slow and expensive, and Decagon or Sierra ask for $250K minimums and 6-month implementations.
Expensive, slow, and zero product context
$30K–$200K per month. 80% annual turnover. CSAT below 70%. Every new agent is a learning curve from scratch.
"The BPO is a mess — they still don't get the product."
LatAm gets answers run through Google Translate
B2B SaaS expands into LatAm and support quality drops 15–20 points. Response time in ES: 18 hours vs. 2 in EN.
"We translate them with Google Translate — and it shows."
Decagon and Sierra don't reach mid-market
6-month setups, annual contracts, $250K minimums, and English-first models. Built for Klarna, not your $20M ARR Shopify brand.
"We want AI, but today's players don't fit us."
From BPO to AI-native in 2 weeks
No setup fees. No minimum contracts. You only pay per resolved ticket.
Onboarding
We connect via API to your Zendesk, Intercom, Gorgias, or Front. We ingest your KB, FAQs, policies, and the last 6 months of tickets.
Custom training
We train the agent on your brand tone, refund policies, product nuances, and edge cases.
Gradual deployment
Start at 20% of volume and ramp to 70% as the model proves quality. Human-in-the-loop by design.
Continuous operation
Monthly reports: deflection, CSAT, response time, and savings vs. baseline. Your Account Manager drives improvement.
Built for B2B SaaS and DTC, not legacy enterprise
Natively trilingual from day one
Spanish, Portuguese, and English at the same quality. Models trained specifically in each language — not translations.
Pre-trained models by vertical
One version optimized for B2B SaaS, another for DTC e-commerce. Start with 60–70% deflection from week one.
Your brand voice, not generic
Custom training on your policies, tone, and nuances. If your brand is warm, the agent is warm. If it's direct, so is the agent.
Smart human-in-the-loop
Contextual escalation when there's ambiguity, critical sentiment, or high-value cases. No all-or-nothing handoffs.
Outcome-aligned pricing
You pay per resolved ticket, not per seat. If the agent doesn't resolve, you don't pay. Incentives aligned from the contract.
SOC 2 · GDPR · no data in the model
Hosting in US/EU. PII is never used for training. Full audit logs of every conversation and agent decision.
Live inside your current stack
Coral connects via API in hours — no platform migration, no process changes. Your human agents see the AI agent as just another teammate in the queue.
What happens when you replace your BPO with Coral
Average data from customers in production. We model your baseline in week 1.
What we get asked on the first call
How long does it actually take to get to production?
2 weeks of onboarding and custom training, followed by 2–3 weeks of gradual deployment from 20% to 70% of volume. Month 1 in production is a realistic target.
What happens with tickets the agent can't resolve?
Contextual escalation to your human team with the full ticket context, prior attempts, detected sentiment, and a suggested response. We never abandon the customer.
How does this compare with Decagon, Sierra, or Ada?
Those players are built for enterprise: $250K minimums, 6-month implementations, and English-first models. Coral is for mid-market teams that need native trilingual support, 2-week setup, and usage-based pricing.
Is my data used to train the general model?
No. Each customer has its own isolated instance and data. PII never leaves your tenant or feeds shared models. SOC 2 Type II and GDPR-ready.
What happens when volumes drop in low season?
Per-resolved-ticket pricing absorbs seasonality. You don't pay for idle capacity like in a BPO. Black Friday or January, you only pay for what gets resolved.
How is this different from a traditional chatbot?
A chatbot follows decision trees. Coral is an agent: it understands context, executes actions (refunds, replacements, plan changes) via API, and learns from your human team's feedback.
Ready to resolve every conversation?
30 minutes with our team. We'll show you a custom agent running on your data in less than a week.