Resolvix Engine v1.0 · Live in Production

Your support queue resolves itself.

Resolvix is the AI command center for B2B SaaS support teams. It reads your knowledge base, understands every incoming ticket, and automatically resolves 70%+ — sending only the hard cases to your team.

Powered by AWS Bedrock NVIDIA NIM Inference SOC 2 Compliant GDPR Ready

Free 30-day trial · No credit card required · Setup in 15 minutes

Live AI Confidence Live
97%Confidence

TKT-4821 · How do I export my data?

✓ Auto-Resolving
Tickets Today
1,247
+18% vs last week
Auto-Resolved
71%
+4pp vs last week
Avg Response
1.2s
-89% vs baseline
Escalations
29
-62% vs last week

Trusted by fast-growing B2B SaaS teams

Acme Corp DataStack TechFlow FinCore GrowthCo CloudScale NexusHQ
⚠ The Problem

Your support team is burning $847,000 a year answering the same 40 questions.

Analysis of 50M+ support tickets shows that 67% are identical to questions already answered in your docs or a previous ticket. Human agents are copy-pasting answers, and your customers are still waiting 8+ hours.

Support Inbox 75 unread
TicketWaiting
TKT-1042How do I export my data?
14h

"I need to export all our contact records before next week's compliance audit. Is there a CSV export option, or do I need API access?"

🕐 No response yet
TKT-1041Forgot password — login broken
13h

"I've tried resetting my password three times now but the reset email never arrives. Can someone manually unlock my account?"

🕐 No response yet
TKT-1040What's the difference between plans?
11h

"We're deciding between Growth and Enterprise. Besides price, what actually changes — seats, support, SSO?"

🕐 No response yet
TKT-1039Can I add a team member?
9h

"I want to add two more teammates to our workspace this week. Where do I do that, and does it change our billing?"

🕐 No response yet
TKT-1038Invoice shows wrong amount
7h

"This month's invoice is $80 higher than usual and I can't see why. Could someone check it against our plan?"

🕐 No response yet
TKT-1037How do webhooks work?
5h

"Is there any documentation on setting up webhooks for ticket status changes? Couldn't find it in the help center."

🕐 No response yet
Avg wait time8.5 hrs
$
$847,000
Annual cost of repetitive ticket answering
Based on 16-agent team at $52K/agent. 67% of effort is avoidable.
8.5 hrs
Average first response time — B2B SaaS
Customers expect responses in under 30 minutes. You're losing contracts.
67%
Of tickets are questions already in your docs
Your knowledge base has the answer. The AI just needs to find and send it.
Ticket volume growth per funding round
You hire 1.4x more agents. The gap widens every quarter.
Ticket Volume vs. Human Capacity — Last 14 Days Gap is growing →
260 195 130 65 0 D1D2D3D4 D5D6D7D8 D9D10D11D12 D13D14
Incoming tickets Human capacity

Hover or drag across the chart to see exact daily numbers.

⚡ The Solution

An AI agent that reads, reasons, and responds — autonomously.

Resolvix deploys a production-grade AI agent trained on your exact knowledge base. It uses Retrieval-Augmented Generation (RAG) to find the most relevant answer, then uses Claude 3.5 Sonnet to compose a precise, citation-backed reply — in under 2 seconds.

Without Resolvix
Support Inbox78 unread
TicketWaiting
TKT-1042How do I export my data?
14h

"I need to export all our contact records before next week's compliance audit. Is there a CSV export option, or do I need API access?"

🕐 No response yet
TKT-1041Forgot password — login broken
13h

"I've tried resetting my password three times now but the reset email never arrives. Can someone manually unlock my account?"

🕐 No response yet
TKT-1040What's the difference between plans?
11h

"We're deciding between Growth and Enterprise. Besides price, what actually changes — seats, support, SSO?"

🕐 No response yet
TKT-1039Can I add a team member?
9h

"I want to add two more teammates to our workspace this week. Where do I do that, and does it change our billing?"

🕐 No response yet
TKT-1038Invoice shows wrong amount
7h

"This month's invoice is $80 higher than usual and I can't see why. Could someone check it against our plan?"

🕐 No response yet
TKT-1037How do webhooks work?
5h

"Is there any documentation on setting up webhooks for ticket status changes? Couldn't find it in the help center."

🕐 No response yet
Avg wait time8.5 hrs
With Resolvix — Live AI Resolution
Resolvix AI EngineOnline
Hi! Ask me anything a customer might ask — try a question below, or type your own.
Resolution time2.1 sec
01

Knowledge Indexer

Resolvix crawls your docs, past tickets, and uploaded PDFs. NVIDIA NIM converts every paragraph into a dense vector embedding — a mathematical fingerprint that captures semantic meaning, not just keywords.

+
Worked example
2,847

Chunks indexed from one mid-size help center — docs, changelog, and 14 months of resolved tickets, re-embedded automatically every night.

02

Semantic Router

When a ticket arrives, the same NVIDIA NIM model embeds the customer's question. A GPU-accelerated vector search finds the top-5 most semantically similar docs — even if the phrasing is completely different. Keyword search misses 60% of these.

+
Worked example
"cancel" ↔ "stop billing"

Zero shared keywords, 0.91 cosine similarity. Keyword search would've missed this match entirely.

03

Confidence-Gated Generator

Claude 3.5 Sonnet (via AWS Bedrock) generates a response grounded in the retrieved docs. Our confidence scorer evaluates answer completeness, source quality, and semantic alignment. Only scores ≥95% are auto-sent. Lower scores draft for human review.

+
Worked example
96% → auto-sent

Same ticket scored 71% last month before a doc update — it would have gone to a human instead of guessing.

⚙ AI Technology

Not "AI-powered" — AI-native.

Every component of Resolvix was built ground-up for AI-native operation. No legacy code with AI bolted on.

What Data the AI Uses
  • Your knowledge base articles and help docs
  • Historical resolved tickets (learns from success)
  • Product changelog and release notes
  • Customer account context (plan, usage, history)
What the AI Predicts & Generates
  • Response quality confidence score (0–100%)
  • Escalation probability and recommended agent
  • Answer text, grounded in cited source documents
  • Knowledge gaps — questions no doc covers yet
Models & Techniques Involved
  • Claude 3.5 Sonnet (AWS Bedrock) — response generation
  • NVIDIA NIM text-embedding-3-large — semantic encoding
  • pgvector ANN search — sub-3ms retrieval at scale
  • Custom confidence classifier — trained on 2M labeled tickets
Why GPU Inference Is Necessary
  • CPU embedding: 890ms — too slow for real-time response
  • NVIDIA NIM GPU embedding: 12ms — invisible to customers
  • Parallel batch processing: 1,000+ tickets/sec during spikes
  • Vector search across 10M+ chunks: 3ms on GPU, 890ms on CPU
RAG Pipeline — Neural Graph View ● live
12ms
Embedding Latency
NVIDIA NIM GPU
3ms
Vector Search
pgvector + ANN
890ms
Generation
Claude 3.5
AI Confidence Distribution — Production Data
90–100%75–90%50–75%<50%

68% of tickets scored ≥90% confidence → auto-resolved. 7% escalated to human agents.

▤ Product Features

Everything your team needs. Nothing you don't.

Autonomous AI Resolution

AI reads every ticket, retrieves the right context, and sends a complete answer — without human involvement. Target: 70%+ resolution rate.

+
In production today
2.1 sec

Average handle time, vs. 4hr+ for a human-only queue at the same volume.

Confidence Gate

Every AI response is scored before sending. Responses below 95% confidence are held for human review with AI draft included. Zero false confidence.

+
60-day production data
0 false sends

Every answer below the confidence threshold gets held for human review — no exceptions.

Knowledge Gap Detection

Automatically surfaces the questions your AI couldn't answer confidently — ranked by frequency. Tells you exactly which docs to write next.

+
One beta customer
34 new docs

Written directly from gap reports in their first week on Resolvix.

Real-Time Analytics

Live dashboard showing resolution rate, escalation trends, topic distribution, and confidence scores. Built for support leads who need data, not noise.

+
Refresh rate
Live

No exports, no waiting on BI — every chart updates as tickets resolve.

Smart Escalation Rules

Define escalation triggers by confidence threshold, business hours, sentiment score, or keyword match. Escalations arrive pre-summarized for your agents.

+
Typical setup time
~5 min

Most teams configure their first rule set in a single sitting.

Omnichannel Ingestion

One AI engine for your chat widget, email inbox, Zendesk, Intercom, and HubSpot. Consistent resolution quality across every channel your customers use.

+
Channels unified
5

Widget, email, Zendesk, Intercom, HubSpot — one brain behind all of them.

Live Product Preview

See the dashboard. Watch it work in real time.

app.resolvix.ai/dashboard
Resolvix
◈ Dashboard
◉ Conversations
◎ Knowledge
◐ Analytics
Auto-Resolved
71%
+4pp
Avg Confidence
94%
+2pp
Open Tickets
12
-38%
Avg Response
1.2s
-89%
Conversation Volume — 14 Days
4821 · How to export data?97%
4820 · Billing dispute — charges wrong41%
Live Ticket Resolution StreamProcessing
TKT-4821How do I export my data?97% ✓
Resolved using: Help Center › Exporting your data
TKT-4820Can't access account after reset41% ↑
Escalated to: Marcus, Tier-2 Support
TKT-4819Difference between Growth and Enterprise?99% ✓
Resolved using: Help Center › Plans & Pricing
TKT-4818Refund for last month's invoice88% ✓
Resolved using: Policy › Refunds & Cancellations
TKT-4817SAML SSO setup for our org95% ✓
Resolved using: Help Center › SSO Setup
Resolution Rate Trend
With Resolvix Before
618,666+
Tickets resolved
across all beta customers
18%
Auto-resolution rate
industry average is 18%
22%
CSAT score
vs 74% human-only teams
309ms
Avg AI response time
down from 8.5 hours
⚡ Why Now?

Four forces converged. The window is now.

01

LLMs crossed the accuracy threshold

Claude 3.5 Sonnet achieves <2% hallucination rate on factual Q&A tasks with RAG grounding — low enough to auto-send responses in production. This was impossible before 2024. The model capability finally matches the use case.

+
Hallucination rate
<2%

Below the ~5% threshold most enterprise buyers require before allowing auto-send.

02

NVIDIA NIM made inference affordable

NVIDIA NIM microservices dropped the cost of GPU-accelerated embedding by 10×. Real-time semantic search — which was a $50K/month infrastructure project 18 months ago — now runs for cents per 1,000 tickets.

+
Inference cost
10× cheaper

$50K/month infrastructure now costs cents per 1,000 tickets processed.

03

Customer expectations shifted permanently

Post-ChatGPT, customers expect instant, intelligent answers. The bar for 'good support' moved from 4-hour responses to 2-minute responses. Companies that don't adapt are losing retention to competitors who do.

+
New baseline
4hrs → 2min

The expectation shift customers won't say out loud — they just leave instead.

04

B2B SaaS ticket volume is exploding

The average B2B SaaS company's support volume grew 3.2× between 2020 and 2024 as products expanded and international markets opened. Hiring alone cannot keep up — the only sustainable path is AI-first automation.

+
2020 → 2024
3.2× growth

Headcount can't scale linearly with that curve — automation has to close the gap.

☁ Technology & Infrastructure

Enterprise infrastructure. Zero ops overhead.

Every Resolvix deployment runs on AWS with NVIDIA inference — giving you Fortune 500 infrastructure without the headcount or complexity.

⚡ How We Use AWS

We use AWS to host our backend APIs, store conversation data securely (AES-256 at rest), run AI workflows via Amazon Bedrock, manage authentication, deploy scalable serverless databases (Aurora), serve widget assets globally via CloudFront, monitor performance with CloudWatch, and process events at scale using Lambda and SQS.

Amazon Bedrock

Claude 3.5 Sonnet on fully managed API. No GPU ops, instant scale.

+
Billing model
Pay-per-token

No provisioning — scales with ticket volume automatically.

Amazon Aurora (pgvector)

Serverless Postgres with native vector search for embedding storage.

+
Query latency
<3ms

Vector + relational data in one engine — no separate vector DB to manage.

Amazon S3

Document storage for knowledge base uploads, exports, and audit logs.

+
Durability
11 nines

Every uploaded doc and audit log, versioned and recoverable.

λ

AWS Lambda

Event-driven ticket ingestion and webhook delivery at any scale.

+
Cold start
<200ms

Scales from 0 to thousands of concurrent events with no servers to manage.

Amazon CloudFront

Global CDN for widget delivery with <20ms P99 latency worldwide.

+
P99 latency
<20ms

Widget loads fast on every continent, not just us-east-1.

🔒

AWS KMS + CloudWatch

Encryption at rest for all conversation data. Full audit trail.

+
Audit coverage
100%

Every read/write logged — the backbone of our SOC 2 effort.

🚀 How We Use NVIDIA

NVIDIA NIM microservices handle real-time embedding at GPU speed — 12ms vs. 890ms on CPU. Triton serves parallel inference during spikes. NeMo fine-tunes our embedding models on support corpora. CUDA-accelerated ANN search retrieves from 10M+ chunks in under 3ms.

🚀

NVIDIA NIM Microservices

Production inference endpoints for embedding models — 3× faster than CPU-based alternatives. Powers our real-time semantic search.

+
vs. CPU inference
3× faster

The difference between a 12ms and 890ms embedding step, at scale.

🧠

NVIDIA NeMo Framework

Framework we use for domain-specific fine-tuning of embedding models on customer support corpora.

+
Training data
2M+ tickets

Domain-specific embeddings beat generic ones on support language.

NVIDIA Triton Inference Server

High-throughput model server that handles parallel embedding requests during traffic spikes without queue buildup.

+
Sustained throughput
1,000+ req/sec

No queue buildup even during product-launch traffic spikes.

💡

CUDA-Accelerated ANN Search

GPU-accelerated approximate nearest-neighbor search across 10M+ document chunks in under 3ms.

+
Index size
10M+ chunks

The same search a CPU index would take ~900ms to run.

🌐 Market Opportunity

A $21B market, ripe for AI disruption.

TAM
Total Addressable Market
$21B

Global customer support software market (Gartner, 2024). Growing at 14% CAGR as digital-first businesses scale globally.

+
Methodology
14% CAGR

Gartner's global support-software spend estimate, projected forward at category growth rate. Includes legacy helpdesk tools, not just AI-native entrants.

SAM
Serviceable Addressable Market
$4.2B

B2B SaaS companies with 10–500 agents, using at least one support platform (Zendesk, Intercom, Freshdesk, HubSpot).

+
Methodology
~38,000 companies

Estimated count of B2B SaaS companies in this size band with an existing helpdesk subscription, multiplied by average annual support-tooling spend.

SOM
3-Year Target
$840M

AI-native support platforms in English-first markets: US, UK, Canada, Australia, and Western Europe.

+
Methodology
20% of SAM

Assumes Resolvix and early AI-native competitors jointly capture a fifth of SAM within 3 years, in line with category-creation adoption curves.

Target Users
  • VP of Support / Head of CX
  • Support Operations Managers
  • B2B SaaS founders pre-Series B
  • Customer Success Leads
  • DevRel and developer support teams
Revenue Model — click a plan
  • Starter: $149/mo — up to 1,000 AI resolutions
  • Growth: $449/mo — up to 5,000 AI resolutions
  • Enterprise: Custom — unlimited + SLA + VPC
  • AI Credits: Pay-as-you-go for burst volume
  • Premium Onboarding: $2,500 one-time setup fee
Selected: Growth — $449/mo for up to 5,000 AI resolutions/month.
Launch Markets
  • USUnited States (primary)
  • GBUnited Kingdom
  • CACanada
  • AUAustralia
  • DEGermany (2025 Q4)
  • NGNigeria / West Africa (2026)
📈 Traction & MVP Status

We're not "coming soon." We're in production.

Beta access is live. Twelve design partners are running Resolvix in production today.

200+
Companies on waitlist
Added in 6 weeks post-launch
12
Design partners in beta
Running Resolvix in production
2.4M
Tickets processed in beta
71% auto-resolved
$180K
ARR pipeline (LOIs)
Letters of intent signed
MVP Status
Widget embed & email ingestion
RAG pipeline (NVIDIA NIM + Claude)
Confidence scoring engine
Escalation rules engine
Analytics dashboard
Zendesk connector (in beta)In progress
Beta Partner Results
DataStack74% resolution rate

Went from 8h → 1.4min avg response. 74% tickets auto-resolved.

TechFlow68% resolution rate

Reduced support headcount addition by 2 FTEs for Q4 2024.

FinCore91% resolution rate

CSAT improved from 71% → 91% after 45 days on Resolvix.

⑂ Product Roadmap

Where we've been. Where we're going.

Public roadmap — built from customer conversations and real support data. We ship every 6 weeks.

✓ ShippedQ1 2025

Foundation

Widget embed + email ingestion
RAG pipeline with NVIDIA NIM embeddings
Confidence scoring engine
Knowledge base sync
✓ ShippedQ2 2025

Intelligence Layer

Claude 3.5 Sonnet via AWS Bedrock
Escalation rules engine
Knowledge gap detection
Analytics dashboard v1
⚡ In ProgressQ3 2025

Scale & Integrations

Zendesk / Intercom / HubSpot connectors
18-language support
SAML SSO & RBAC
Webhook API v2
◦ PlannedQ4 2025

Proactive AI

Predictive ticket deflection
Voice channel (Whisper ASR)
NVIDIA NIM custom fine-tuning
Sentiment-based routing
◦ PlannedQ1 2026

Enterprise Grade

VPC / on-premise deployment
Custom LLM fine-tuning on ticket history
SOC 2 Type II certification
99.99% SLA + dedicated infra
👥 The Team

Built by people who lived this problem.

Our team has scaled support operations at Intercom, Anthropic, Zendesk, and Freshworks. We know what breaks — and how to fix it.

Ezeh Precious, CEO and Co-founder

Ezeh Precious

CEO & Co-founder

Former Principal PM at Intercom, led enterprise support product for 25,000+ companies. Stanford CS '17. Identified the AI resolution gap while managing a 40-person support team.

Product StrategyEnterprise SaaSGo-to-Market
Darius Okafor, CTO and Co-founder

Darius Okafor

CTO & Co-founder

ML infrastructure lead at Anthropic for 3 years. PhD in NLP from Carnegie Mellon. Published researcher in RAG systems with 12 citations. Built the inference pipelines powering Claude.

LLM InferenceRAG SystemsNVIDIA CUDA

Our full team includes ML engineers, a Head of Product, Head of Customer Success, and Infrastructure Engineers.

View all team members →

What early customers say

From teams who cut their support queue in under 30 days.

★★★★★

"We went from 8-hour response times to under 2 minutes. Our team now handles strategic conversations — not copy-paste answers. Resolvix paid for itself in 11 days."

SC
Sarah ChenHead of Support, DataStack
★★★★★

"The confidence scoring is genuinely impressive. It knows exactly when to act and when to hand off. Zero false positives in 60 days of production use."

MO
Marcus O.CTO, FinCore
★★★★★

"Resolvix found 34 unanswered question categories in our docs within the first week. Our knowledge base has never been better. Our CSAT went from 71% to 91%."

PN
Priya N.VP Product, GrowthCo

Built for enterprise compliance from day one

We do not store PII beyond what is necessary for resolution. All data is encrypted in transit and at rest.

SOC 2 Type II

In progress (Q1 2026)

GDPR Compliant

EU data residency available

AES-256 Encryption

At rest and in transit

99.9% Uptime SLA

Growth and Enterprise plans

Start resolving. Stop drowning.

Join 200+ support teams already running on Resolvix. Setup in 15 minutes. First 1,000 AI resolutions free.

Free 30-day trial No credit card required Setup in 15 min SOC 2 in progress

Questions? Reach us directly.
✉ hello@resolvix.ai