Resolve Issues Faster. Delight Customers.

Packaged tools cover 80% of use cases well. The 20% where custom builds pay off: when your ticket entities don't fit the standard schema (cargo shipments, property claims, patient cases), when you need deep product-context in the agent view that no integration covers cleanly, when your SLA rules have complexity that packaged tools can't express, or when you're processing tens of thousands of tickets per day and per-ticket API costs compound. We'll give you an honest comparison: extending packaged tools is often the right answer, and we do that work too.

The failure mode in AI deflection is a confident wrong answer. We address this by classifying intent before retrieval, setting a confidence threshold below which the bot escalates to a human rather than guessing, and logging every deflection outcome so you can tune the threshold over time. We also make the handoff explicit, customers know they're talking to an assistant and can request a human at any point. Deflection rates of 30–50% on low-complexity ticket categories are realistic without a significant increase in CSAT complaints when the fallback path is reliable.

We architect ingestion as a queue-backed pipeline rather than synchronous API calls: tickets enter a durable queue, are processed by workers that scale horizontally, and are assigned to agents in SLA-priority order. This decouples ingestion speed from processing capacity. Volume spikes fill the queue rather than dropping requests, and SLA clocks start when the ticket is created, not when it's assigned, so you can see exactly which tickets are at risk and prioritize accordingly.

Yes. The most valuable support integrations pull account status, billing tier, product usage data, and recent activity into the ticket view automatically. We typically build this as a context API, a single call that returns everything about the customer in the ticket, rather than point integrations between each system. This makes the agent view consistent and reduces the number of tabs an agent has to check before responding. We've integrated with Salesforce, HubSpot, Stripe, Chargebee, and custom product backends.

A focused MVP with ticket ingestion from one or two channels, basic routing, SLA enforcement, an agent interface and reporting falls in our MVP / Prototype range: $25K to $60K over 4 to 8 weeks. Full platforms with multi-channel ingestion, deep product integrations and a customer-facing help center are Production Application builds at $60K to $200K over 3 to 5 months; AI deflection at scale moves the work into our AI / ML range of $80K to $300K+. We scope in phases: the first phase delivers a working system your team can use before the full budget is committed.