Giga vs. Fin

Giga outperforms Fin on resolution, depth, and control.

Fin answers questions on top of your helpdesk. Giga resolves the whole workflow across your live systems, one agent, on any stack.

Talk to sales
DoorDashCapital.comToastFlexRemedy MedsPostman
The honest comparison

When the workflow gets hard, Fin hands it back.

Resolution model
Giga · Autonomously resolves multi-step workflows via live systems
Fin · Answer/deflection-oriented; counts human handoffs as billable outcomes
Multi-system actions
Giga · Acts across any system; browser agents where no API (“no integration army”)
Fin · Actions via configured Procedures/connectors; deep orchestration is DIY
Independence
Giga · Channel- and helpdesk-agnostic: one agent over any stack
Fin · Built around Intercom; standalone on other helpdesks is sales-led with Intercom underneath
Voice
Giga · ~400ms, accent-robust, 90+ languages, mid-call switch
Fin · Fin Voice is newer, fewer languages
Hallucination safety
Giga · Correction agent mid-response; 4x lower than frontier models
Fin · Grounding/guardrails only; no real-time correction
Time to deploy
Giga · First agent ~10 min; production <2 weeks with an FDE
Fin · Fast for FAQ deflection; complex procedures need ongoing config
Pricing
Giga · Outcome-based, scoped to the KPI you move
Fin · Priced per outcome, even human handoffs count, so cost scales with volume

From enterprise evaluations and teams who ran both. Bring your scenario, we’ll show you live.

Industry leading metrics

Real numbers, in production.

  • RESOLUTION

    Over 90% resolved

    Resolved in your systems, not deflected to an article. 10–25% Containment lift in the first 120 days

    EACH DOT = 1% OF CONVERSATIONS
    90% Resolved10% To Human Agent
  • RESPONSE TIME

    Answers in under a second

    400ms voice response, noise- and accent-robust, in 90+ languages.

    TIME TO FIRST RESPONSE
    5.0sBEFORE
    instantHOLD TIME ELIMINATED
    0.4sAFTER
  • ACCURACY

    4x lower hallucination rate

    A dedicated correction agent pulls drift back mid-response, no other platform ships it.

    HALLUCINATION RATE VS. FRONTIER MODELS
    4xBEFORE
    −75%DRIFT CORRECTED
    1xAFTER
Customers

Teams run the eval. They pick Giga.

Their hardest cases, multi-party and real-time, with payments and refunds in scope.

DoorDashMarketplace
“Partnerships like this are critical to delivering better outcomes for consumers on a global scale.”
Andy Fang, Co-Founder at DoorDash
Andy FangCo-Founder, DoorDash
A DoorDash order handed off at a customer’s door
  • FlexFlexConsumer finance

    Chose Giga head to head on voice, then expanded into chat, +20 points of resolution in two weeks.

  • ToastRestaurant & retail

    Voice agents that resolve complex issues in real time, with clean handoff to your team when needed.

  • Remedy MedsTelehealth

    Confirms, books, and rebooks appointments, and reaches out to keep patients on their care.

FAQs

Frequently asked questions

Still have questions?

Many teams add Giga for the hardest, multi-system workflows Fin hands back, then consolidate. Giga runs on any stack and resolves in your live systems, not just answers on top of the helpdesk.

BOOK A DEMO

Bring your hardest workflow. We’ll resolve it live.

Name the KPI you want to move, and we’ll show you Giga resolve your hardest multi-system cases, on any stack.

Comparisons based on independent testing conducted by Giga customers.

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Fin Alternative — Giga vs. Fin