HybridDot
●  UTCStart a project →
LIVE · Conversational RAG · Production deployments · CX, BFSI, Healthcare

Production RAG that resolves tickets 60 to 80% faster, without letting hallucinations reach customers.

RAG-grounded agent assist for ticket triage, voice deflection, and frontline support. Built with retrieval quality monitoring, hallucination detection, and explicit escalation gates so the system declines to answer when it shouldn’t.

In production at Feedbird. Multi-tenant SaaS, AI content automation.

Free call. No sales script. 24-hour reply.
Feedbird · Multi-tenant SaaS · 60 to 80% faster resolution range · Hallucination detection built in
02
// 02/WHY YOU’RE HERE

You’ve tried RAG. It hallucinated in production.

Demos look great. Production hits the wall on hallucinations, edge cases, and brand-voice drift. Many CX teams have tried at least one RAG vendor and quietly turned it off after three months.

Most production failures come from three sources: weak retrieval (the model can’t find the right answer), no evaluation harness (you don’t know it’s wrong until a customer complains), and no escalation path (the system tries to handle queries it shouldn’t). Prompt engineering doesn’t fix any of them.

You don’t need another RAG demo. You need a system that knows when to answer, when to escalate, and when to admit it doesn’t know.

03
// 03/WHAT THE SYSTEM DOES

Production-grade RAG with retrieval, escalation and monitoring built in.

  • 01

    Retrieval Quality Monitoring

    Continuous evaluation of retrieval results against ground truth. Surfaces drift, gap-detection, and source-coverage issues before they reach customers.

  • 02

    Hallucination Detection

    Confidence scoring on every response. The system flags low-confidence outputs and routes them to human review instead of guessing.

  • 03

    Explicit Escalation Gates

    Pre-defined escalation rules at the architecture level, not the prompt level. Queries the system shouldn’t handle (regulatory language, sensitive accounts, edge cases) route to a human automatically.

  • 04

    Brand-Voice Calibration

    Tuned to your existing customer-facing content during pilot. Voice fidelity monitored in production with drift alerts.

04
// 04/WHAT IT PRODUCES

Two measured outcomes. One named deployment.

  • 01
    60 to 80% faster
    Ticket resolution time
    Deployed at SaaS-volume across multi-tenant platforms
  • 02
    30 to 50% deflection
    Eligible Tier-1 ticket volume routed to self-service or auto-resolution
    Deployed at production scale with brand-voice calibration
Anchor deployment

Feedbird. AI Content Automation Platform.

Multi-tenant SaaS. Video-to-post pipeline with brand voice calibration. RAG running in production at scale. Integrated retrieval monitoring, hallucination detection, escalation gates active.

Directional ranges from delivered work and internal benchmarks. Specific numbers shared with qualified buyers on diligence calls. Results vary by workflow, data quality and adoption.

// 05 · let’s talk

Rebuilding after a previous RAG vendor failed?

  • Reply within 24 hours, often much faster
  • Free 30-minute call. No sales script.
  • Honest scope and timeline, including when we’re not the right fit
06
// 06/CONVERSATIONAL RAG QUESTIONS

Common questions.

07
// 07/HOW IT’S BUILT

The system, layer by layer.

Conversational RAG architecture. Inputs (chat, voice, email, API, knowledge base) flow into a retrieval layer, then inference plus safety, then a routed output with auto-resolved responses, escalations, audit logs, and analytics.
Inputs → Retrieval → Inference + Safety → Output + Audit. Hallucination gate and human escalation built into the routing layer, not bolted on after.
  1. A

    Retrieval Layer

    Vector stores · Semantic indexing of your knowledge base · Embedding models tuned for support language · Citation trails on every response

  2. B

    Orchestration Layer

    Triage routing · Tool selection across helpdesk, CRM, and voice platforms · Escalation gates to human agents on low-confidence queries · Human-in-the-loop review on flagged cases

  3. C

    Compliance Layer

    Audit logging on every response · Brand-voice evaluation harnesses · Hallucination detection · Drift monitoring with alerts

  4. D

    Integration Layer

    Helpdesk APIs (Zendesk, Intercom, Freshdesk, Salesforce Service Cloud) · CRM bridges · Voice platform connectors (Genesys, Five9, Twilio Flex)

  5. E

    Deployment Layer

    Region-specific hosting · Multi-tenant for SaaS deployments · Single-tenant for enterprise · SOC 2-aligned infrastructure

Same architecture across BFSI, Healthcare, and CX deployments. Adapted to industry context, not rebuilt for each.

Senior engineers. Production from day one.