Relevance AI
relevanceai.com
Actively hiring
Low-Code & No-Code Platforms
AI Agents
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Overview
News
Technologies
Salaries
Products
People
Growth
Offices
Jobs
Financials
Funding and backers
Total raised
$39M
2 rounds on record
Latest round
$24M
Series B · May 2025 · 17 mo ago
Team
51-200
employees, estimated range
Hiring now
1
open roles
Backers
4
Bessemer Venture Partners, Archangel Ventures
The money's age
Due for its next round
17 months since the last round · hiring slowed
Momentum
15/100
in the news
Last sign of life
this month
a posting or a news item
The story so fareach stage dated by its source: the company's releases, the press, registers, filings
May 6, 2025
Raised a round Series B $24M · YahooFinance
Dec 13, 2023
Raised a round Series A $15M · SmartCompany
Feb 4, 2023
Launched on Hacker News Show HN: Ask Relevance – no-code GPT QA on data, managed Vector search and GPT
2017
Founded
Tractionpublic signals, read monthly
Funding rounds
| Round | Date | Amount | Investors | Source |
|---|---|---|---|---|
| Series B | May 2025 | $24M | — | YahooFinance |
| Series A | Dec 2023 | $15M | — | SmartCompany |
Registers and programsofficial lists and records that name the company
| Legal entity | OnSearch Pty Ltd | its site |
Backed byfrom the funds' portfolios and accelerator catalogs
Bessemer Venture Partners 
Archangel Ventures 
Galileo Ventures 
Insight Partners Investors in similar startupsfunds that back the companies most like this one
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Overview
Relevance AI is an Australian software company that runs a no-code platform for building AI agents and multi-agent teams that carry out business tasks such as sales prospecting, customer support and operations work. The platform is aimed at operations teams and subject-matter experts rather than developers, with offices in Sydney and San Francisco and staff in Barcelona. The company is headquartered in Sydney, New South Wales, Australia.
News
Why Relevance Is Becoming Every Brand's Competitive Advantage
The competitive landscape is shifting, with businesses now focusing on relevance as the next frontier beyond personalization. While personalization identifies "who" a customer is, relevance goes further, asking "what" they need right now by combining iden
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Report
Maximum Marginal Relevance & Elastic: Diversifying search results
Learn about Maximum Marginal Relevance (MMR) and how to implement it with Elasticsearch and Python.
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Report
Mixing numeric attributes into text search for better first-stage relevance
turbopuffer now allows you to combine attribute values into the scoring function of text queries. Ranking by attribute helps achieve better relevance in the first stage with the same scalability characteristics as BM25.
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Report
Report
EXCLUSIVE: Leaked Deck Reveals StackAdapt's Playbook for ChatGPT Ads
The DSP dangles ChatGPT ad placement driven by prompt relevance and CPMs range from $15 to $60, with a $50,000 minimum spend required for the pilot.
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Report
Using LLMs to amplify human labeling and improve Dash search relevance
How we train Dash's search ranking models with a mix of human and LLM-assisted labeling.
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Report
HPPIE: RAG Without Persona Modeling Fails Patient Clinical Relevance
HPPIE fuses persona modeling into the RAG pipeline to deliver patient-specific health content. 2nd of 300+ at a Global AI Hackathon.
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Report
How we optimized Dash's relevance judge with DSPy
We used DSPy to turn prompt engineering for our relevance judge into a measurable, automated optimization loop, improving task performance, cost, and how reliably it works in production.
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Report
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Tech stack
Technologies named in job postings at Relevance AI over the last 12 months, by layer, with the share of postings for each.
Technologies in use
35
Postings analysed
17
Stack modernity
78/100AI adopter
Languages
JavaScript53%
Node JS53%
TypeScript53%
Python41%
Frameworks & libraries
Express53%
React.js53%
Vue.js53%
Dapr6%
Databases
PostgreSQL53%
Cloud & platforms
Databricks100%
AWS53%
Kubernetes53%
Vercel53%
AI & ML
Claude29%
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Full Relevance AI tech stack
35 technologies · by team · pay by technology · changes · similar stacks
Growth
Hiring Momentum
64/100
Growing
Open positions
1
0 opened / 5 closed in 30 days
Median time-to-fill
54 days
faster than 26% of the market
ATS activity
Every ~4 hours
Today
Hiring Dynamics
+100%
Hiring Focus
The percentage next to each role is its share of the company's job openings over the last 90 days; the arrow shows the shift versus the previous period.
AI/ML
15% ▼
Product
15% ▼
Marketing
15% ▲
Sales
15% ▼
Backend
8% ▼
Security
8% ▼
Activity Timeline
Added Agile to stack
Sep 2026
Added Tool Use to stack
Sep 2026
Added HubSpot to stack
Sep 2026
Added Agentic Workflows to stack
Sep 2026
Added Relevance AI to stack
Sep 2026
Added LinkedIn to stack
Sep 2026
Added Canva to stack
Sep 2026
Added Model Context Protocol to stack
Aug 2026
Added Least Privilege to stack
Aug 2026
Added Function Calling to stack
Aug 2026
Added Context Engineering to stack
Aug 2026
Added IAM to stack
Aug 2026
Offices
Where the company hires and what each office is for
Cities
1
Hiring now
1
Countries
1
Busiest office
Sydney
Sydney
Australia
HQ
1 open roles 6 posted in 90 days 100% engineering 50-200 est. staff
hires for AI/ML
Earlier presence
San Francisco, United States
Barcelona, Spain
Jobs
≈ $107k – $274k per year (Estimated) • Equity • Hybrid • Full-Time • Sydney
Python
JavaScript
TypeScript
Node JS
Express
Databases
PostgreSQL
Databricks
AI/ML
Cursor
Claude Code
AI Agents
OpenAI Codex
LLM Guardrails
Relevance AI
Frontend
Vue.js
React.js
DevOps
Terraform
GitHub Actions
Vercel
Datadog
CI/CD
AWS
Kubernetes
Platform Engineering
Octopus Deploy
Design
Canva
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