Coralogix
Coralogix is an AI-native observability platform and data lake that ingests, stores and queries all telemetry for unified monitoring, analysis and cost-optimized retention.
- Business Profile
- Founders & Team5 sources scanned
- Market Size12 sources scanned
- Competitor Research5 sources scanned
- Funding14 sources scanned
- Momentum8 sources scanned
- Customer Sentiment5 sources scanned
- AI Visibility
- Risks & Red Flagspublic record checked
Summary
Worth a closer lookCoralogix is an AI-native observability and telemetry data-lake play that wins on in‑stream processing, customer‑owned storage and consumption-based pricing — a clear cost/latency wedge versus Logz.io, Sumo Logic and New Relic. With disclosed ARR > $100M, >5,000 customers (implied ACV ≈ $20k) and an accelerating public momentum arc (G2 Winter 2026, $115M Series E in Jun 2025 then a $200M Series F on Jun 3, 2026; total funding $550M at a $1.6B post), the company has moved beyond early‑adopter traction into scale. The single biggest tension is product breadth: reviews and public signals show logs are strong but metrics/traces are less mature and the UI/learning curve frustrates some customers — a risk when competing with New Relic, Grafana and Honeycomb on full‑stack observability. First meeting should focus on unit economics, roadmap for metrics/traces, and how in‑stream/storage differentiation translates to durable enterprise contracts.
Bull case
- Clear market momentum and capital: $200M Series F (Jun 3, 2026) following a $115M Series E (Jun 17, 2025), totaling $550M raised and a reported $1.6B valuation — gives room to scale GTM and product.
- Commercial traction at scale: disclosed ARR > $100M and >5,000 customers (implied ACV ≈ $20k) demonstrating adoption beyond pilots into commercial accounts.
- Product and cost wedge: in‑stream processing plus customer‑owned storage and consumption pricing deliver concrete TCO wins cited by customers (lower MTTR and storage cost).
- Strong customer sentiment: G2 rating 4.6/5 with repeated praise for fast, engineer‑level support and real‑time/no‑index analytics.
Watch-outs
- Product breadth gap: public reviews and signals show metrics/traces are less mature than logs — weakens claims of 'unified telemetry' against Honeycomb and New Relic.
- User experience friction: recurring complaints about a steep learning curve and UI/performance issues could slow expansion and increase churn.
- Competitive pressure from incumbents and OSS: New Relic, Grafana (Loki/Tempo) and Honeycomb offer scale, ecosystem integrations or OSS flexibility that can blunt Coralogix's go‑to‑market.
- Financial transparency unknowns: runway, unit economics (CAC, LTV), gross margins and durability of consumption‑based revenue are not publicly disclosed.
Company profile
Customers on site
Pricing
Not publicly disclosed. The company website does not list its pricing on any of the 6 pages we read.
Target segments
Key features
- Application Performance Monitoring (APM)
Monitors application performance including serverless APM, service map and continuous profiling.
- Real User Monitoring (RUM)
End-user performance monitoring with session replay, error tracking and core web vitals.
- Infrastructure Monitoring
Infrastructure health and fleet monitoring with explorer and fleet management capabilities.
- Log Analytics
Log ingestion, enrichment, parsing and templating for analysis and troubleshooting.
- AI Observability
AI-driven observability features (includes AI Discovery, AI Guardrails, AI Security & Compliance).
- Security Information and Event Management (SIEM)
Security monitoring and compliance reporting capabilities.
- Managed Detection and Response (MDR)
Proactive threat detection and response services.
Stats they publish
Testimonials
“There were problems that could’ve been caught earlier, and were not caught, because we didn’t have the right visibility,” Alain says.”
Alain Adler · Head of Engineering at BetterHelp“Pretty much [we] just scheduled a meeting with one of their experts, we talk about what we’re doing…and we’re all set,” Alain said.”
Alain Adler · Head of Engineering at BetterHelp“Coralogix changed the way we work,” Alain said.”
Alain Adler · Head of Engineering at BetterHelp
Social accounts
Compliance & certifications
Corporate identity & contact
- Trade name
- Coralogix Ltd.
Founders & Team
6- Ariel AssarafFounderCEO & Co-founder
- Yoni FarinFounderCTO & Co-founder25+ years of expertise in software development, big data, and distributed systems.
- Chetan ChaudharyCROOver two decades of experience propelling growth for prominent technology firms, leading sales, customer success, marketing, partnerships and revenue operations.
- Yael Sapir-ZahaviCHROOver two decades in HR across startups (Tailor Brands) and large corporations (Amdocs); holds a B.A. in Psychology and an M.A. in Human Resources from Tel Aviv University; Executive Coach with 15+ years of experience.
- Eran HadadCFOBegan career at KPMG; served as Senior Accountant at Micron Israel; spent nearly a decade in senior finance roles at Kaltura.
- Piyush VermaHead of Product Strategy20+ years in software development and site reliability engineering; founder and CTO of Last9; has founded several startups and worked with SaaS companies including DataStax and TrustingSocial.
Coralogix’s public leadership (per the company’s About page and company blog) includes co-founders Ariel Assaraf (CEO) and Yoni Farin (CTO) plus senior executives Chetan Chaudhary (CRO), Yael Sapir-Zahavi (CHRO), Eran Hadad (CFO) and Piyush Verma (Head of Product Strategy). The list is drawn from Coralogix-controlled pages.
- Founders are taken from Coralogix's own About page (Ariel Assaraf and Yoni Farin). Several third-party databases and profiles (e.g., Tracxn, Craft, Crunchbase) list additional founders or different founder attributions (names such as Lior Redlus and Guy Kroupp); those aggregator-only attributions were not treated as authoritative and were omitted.
- Only people named on Coralogix-controlled pages (About page and company blog) are included. Other leadership names that appear only in third-party aggregators or profiles were excluded to avoid misattribution.
- No explicit company headcount was stated on the company pages provided; team_size is left blank.
Market Size
Published market research places the global AI-in-observability / observability-platform vendor market in the low-to-mid tens of billions over the next decade (representative published projection: USD 10.7B by 2033 for AI in observability). Coralogix is a growth-stage player with disclosed ARR > USD 100M and >5,000 customers (implied ACV ≈ USD 20k); however, no grounded, public count of the total target customer population or published product pricing was available to produce a defensible bottom-up SAM or a grounded SOM.
- market.us (report page quoting AI in Observability market) ↗The Global AI in Observability Market size is expected to be worth around USD 10.7 Billion by 2033, from USD 1.4 Billion in 2023, growing at a CAGR of 22.5% during the forecast period from 2024 to 2033. · Global · 22.5% CAGR
- Technavio ↗The ai in observability market size is valued to increase by USD 2.92 billion, at a CAGR of 22.5% from 2024 to 2029. · Global (multi-region breakdown in report) · 22.5% CAGR
- Mordor Intelligence (observability market report page) ↗The observability market size was valued at USD 2.9 billion in 2025 and estimated to grow from USD 3.35 billion in 2026 to reach USD 6.93 billion by 2031, at a CAGR of 15.62% during the forecast period (2026-2031). · Global · 15.62% CAGR
- Coralogix disclosed ARR (most recent)Annualized revenue > USD 100 million (June 2026)https://techcrunch.com/2026/06/03/coralogix-raises-200m-in-race-to-build-the-monitoring-layer-for-ai-agents/
- Coralogix disclosed customer count (most recent)Over 5,000 customers globallyhttps://coralogix.com/blog/coralogix-raises-200m-to-scale-the-observability-backbone-for-theage-of-ai/
- Implied current average revenue per customer (ACV) for CoralogixImplied ACV = ARR / customers = USD 100M / 5,000 ≈ USD 20,000 per year (rounded)Coralogix ARR and customer counts above
- Why SAM is not estimated bottom-up hereNo grounded, public global count of the target set of mid-to-large engineering/SRE/platform teams (or a published ACV/pricing schedule) was available to build a defensible bottom-up SAM; therefore SAM is left null rather than guessed.
- TAM is drawn from published 'AI in observability' and broader 'observability platform' vendor-market reports; reported totals vary substantially by publisher and by how narrowly they define 'observability' (AI-specific vs. full observability tools), so the cited USD 10.7B figure should be read as one published global projection, not a single-source truth.
- SAM and SOM are set to null because a defensible bottom-up SAM requires either (a) a grounded count of target customer organizations at the target company-size and geography or (b) Coralogix's published ACV/pricing — a reliable, public ACV/pricing schedule was not available. Implied ACV (USD ~20k) is shown for context but was not used to produce a bottom-up SAM.
- Different research houses report materially different market bases and years (examples above: USD 2.9B in 2025, USD 6.93B by 2031, USD 10.7B by 2033); comparisons require aligning definitions (AI-in-observability vs. full observability tools/platforms).
- Some cited reports are forecast projections (multi-year horizons) and use different segmentations (component, deployment mode, enterprise size); each figure's regional scope is 'Global' unless otherwise stated.
- SOM not estimated: although Coralogix shows clear traction (Series F / large raise, ARR > USD 100M, thousands of customers), producing a realistic obtainable share requires a bottom-up SAM or clearer ICP counts; producing a SOM without that would be speculative.
Competitors
Top 5Competitive set ranges from large incumbents and OSS tooling (New Relic, Grafana) to log-analytics and developer-focused rivals (Logz.io, Sumo Logic, Honeycomb). Coralogix sits as an AI-native, cost-focused unified telemetry platform with in-stream processing.
- Logzlogz.io ↗AI-powered observability (logs, tracing, infra); Coralogix matches breadth but differentiates with in‑stream processing and customer‑owned storage for lower cost and faster queries.
- Honeycombhoneycomb.io ↗High-cardinality, event-driven observability for deep debugging; Coralogix offers broader unified telemetry and cost-optimized retention, while Honeycomb wins on exploratory query granularity.
- New Relicnewrelic.com ↗Full-stack APM and observability with large install base and free tier; Coralogix competes on cost and in‑stream analytics, New Relic wins on scale and ecosystem integrations.
- Grafanagrafana.com ↗Open-source visualization and observability stack (dashboards, Loki/Tempo); Coralogix provides managed unified telemetry and in‑stream analytics, Grafana wins on OSS flexibility and dashboards.
- Sumo Logicsumologic.com ↗Cloud-native log analytics and security-focused observability; Coralogix undercuts on storage cost and in‑stream processing, Sumo Logic wins on enterprise security/compliance features.
Funding
- SeedAugust 17, 2014Joule VenturesStageOne VenturesCrunchbase (web search)
- Non-Equity Assistance (program)March 13, 2016Crunchbase (web search)
- Series ANovember 26, 2019Aleph leadStageOne VenturesJoule Ventures2B AngelsCrunchbase (web search)
- Series E$115MJun 17, 2025Coralogix (company blog) ↗
- Series F$200MJune 3, 2026Advent International leadAleph leadBrighton Park Capital leadCrunchbase (structured data) ↗
Coralogix publicly disclosed a $115M Series E (Jun 17, 2025) and a $200M Series F (Jun 3, 2026). Earlier rounds (Seed, 2014; Series A, 2019) are recorded by Crunchbase but amounts are not disclosed here; company and press report total funding of $550M and a $1.6B valuation after the Series F.
- The company and multiple press outlets report a $550M total raised and a $1.6B valuation after the June 2026 Series F; the itemized rounds in this file (Series E + Series F = $315M) leave a gap because earlier rounds (seed, Series A and others) are recorded without disclosed amounts in the provided text.
- Seed (Aug 17, 2014) and Series A (Nov 26, 2019) are taken from a Crunchbase web-search summary in the corpus; those entries have no direct [SOURCE <url>] marker in the provided text, so their url fields are null and amounts are undisclosed here.
- Crunchbase structured data anchors the Series F round (listed leads include Advent International, Aleph, Brighton Park Capital), but multiple press accounts (company blog, TechCrunch, SecurityWeek) state the Series F was co-led by Advent and CPPIB (Canada Pension Plan Investment Board). The lead-investor list above follows the Crunchbase structured-data fragment; press disagreement is noted.
- Series E lead investor is not named in the company blog post excerpt included here; some tracker summaries in the corpus attribute the Series E to NewView Capital but those summaries are not tied to a [SOURCE <url>] marker in the provided text and were therefore not assigned as the round lead.
- The 'Non-Equity Assistance' entry is a program mention (from Crunchbase summary) rather than a disclosed equity/debt raise; it is included as a non-equity program event.
- Some tracker databases in the corpus show different totals (PitchBook/Tracxn snippets show ~$346M–$350M); public/company statements claim $550M — the public/company total was used as the headline total and the discrepancy is listed above.
Momentum
- FundingJune 3, 2026Coralogix announced a $200M Series F to scale its AI-native observability platform.GlobeNewswire ↗
- MilestoneJune 03, 2026Coralogix said it is trusted by more than 5,000 customers worldwide.GlobeNewswire ↗
- AwardWinter 2026Ranked #1 in the G2 Momentum Grid for Observability Software and secured 192 badges in G2 Winter 2026.Coralogix
- FundingJune 17, 2025Coralogix previously raised $115M in a Series E (2025).Coralogix (blog) ↗
Coralogix shows accelerating public momentum: a $200M Series F was announced June 3, 2026 (company press release and widespread press coverage), building on a $115M Series E in June 2025 and recent product/market recognition (G2 Winter 2026).
- Primary recent signals are well-covered (company release + independent press) but some supporting items in the snippets lacked explicit source URLs; where the URL was unclear it is left null.
- Valuation reporting varies across outlets (some mention $1.6B, some do not disclose); that inconsistency is in the press coverage.
- This extract includes only dated public events present in the provided text; other company activity may be unreported here.
Customer Sentiment
11- Customer support qualityUsers repeatedly praise fast, engineer-level support (24/7) and proactive, white-glove assistance.“24/7 engineer-level support with 17-second median response time”CheckThat.ai ↗
- Real-time visibility / faster MTTRNo-indexing, in-stream analytics and unified telemetry reportedly reduce time to detect and resolve incidents.“The real-time visibility into metrics and traces in one place significantly reduced our mean time to detect and resolve issues.”CheckThat.ai ↗
- Cost efficiency / consumption pricingCustomers cite consumption-based pricing and S3 archive ownership as drivers of lower observability TCO versus competitors.“Coralogix helped us control observability costs while still maintaining deep visibility across our distributed systems”G2 ↗
- Integrated logs + metricsUsers value the tight integration of logs and metrics (and traces) for faster root-cause analysis.“Integrated Logs and Metrics Supercharge Root-Cause Analysis”G2 ↗
- ML-driven anomaly detectionML-powered anomaly detection and real-time log insights are cited repeatedly as differentiators.“ML-powered anomaly detection and real-time log insights are the most-cited differentiators”CheckThat.ai ↗
- User interface (some users)Several reviewers describe the UI as pleasant and user-friendly for building dashboards and queries.“The Coralogix UI is pleasant to use and very user-friendly.”G2 ↗
- Steep learning curveMultiple reviewers report a meaningful learning curve, particularly for advanced alerting and complex features.“Users find the learning curve steep , making it challenging for beginners to navigate and understand all features effectively.”G2 ↗
- UI/UX and performance frictionSome users report UI/UX shortcomings and slow performance (delays loading, high memory usage, log retrieval issues).“Users report slow performance with Coralogix, facing delays in loading, high memory usage, and log retrieval issues.”G2 ↗
- Metrics & traces maturitySeveral reviews flag metrics and traces as less mature than the logs product, recommending validation for heavy metrics/trace use cases.“Metrics and traces products less mature than logs”CheckThat.ai ↗
- Cost predictability during spikesConsumption pricing can cause unpredictability in high-volume or burst scenarios according to multiple users.“Cost predictability challenges during volume spikes”CheckThat.ai ↗
- Integration / ecosystem complexityUsers note that multi-source integrations and a relatively small public community/ecosystem can complicate onboarding and advanced use cases.“Multi-source integration can be complex”CheckThat.ai ↗
Public reviews are largely positive: customers consistently praise fast, engineer-level support, real-time/no-index analytics that reduce MTTR, and consumption-based pricing that lowers TCO. Recurring complaints focus on a steep learning curve, some UI/performance friction, and that metrics/traces are less mature than the logs capability.
- Most signal comes from enterprise review platforms (G2, Gartner Peer Insights, AWS Marketplace); some aggregator pages (CheckThat.ai) consolidate multiple platform stats and may duplicate counts.
- Several platforms referenced have very small sample sizes per aggregator (e.g., Capterra: 1 review, TrustRadius: 5 reviews) and should not be over-weighted.
- Users flag unverified limits at very high throughput and metrics/traces scale; those specific scale claims are not uniformly confirmed by public reviews.
AI Visibility
We ask ChatGPT WITH web search about the company and show its answers plus the sources it cited — the real AI-search experience. The key signal is share of voice: does the company come up when AI is asked about its space, not just when asked by name.
Models asked ChatGPT · web search
Accuracy of what AI said: Accurate — The assistant correctly describes Coralogix as an AI-native observability/data-lake platform and its positioning; funding, valuation, and specific headquarter/staff numbers in the DIRECT answer are plausible but not confirmed by the provided profile.
Coralogix is a Boston-headquartered software monitoring company founded in 2014 by CEO Ariel Assaraf and CTO Yoni Farin. The company specializes in observability solutions, offering a real-time streaming analytics pipeline that provides monitoring, visualization, and alerting capabilities without the challenges of indexing and excessive costs. This approach allows users to establish various data pipelines per use case, delivering profound insights at a significantly lower price. (gartner.com)
As of June 2026, Coralogix has raised a total of $550 million in funding, including a recent $200 million Series F round led by Advent and the Canada Pension Plan Investment Board (CPPIB), valuing the company at $1.6 billion post-money. The company employs over 600 people globally, with significant offices in the U.S., Israel, and India. (techcrunch.com)
Coralogix's platform is trusted by over 4,000 teams worldwide, including notable clients such as IBM, Tradeweb, and JFrog. The platform processes over 3 million events per second across more than 500,000 applications globally. (coralogix.com)
In the evolving landscape of AI, Coralogix is positioning itself as a key player by offering AI-native observability solutions. The company emphasizes the importance of monitoring AI agents and autonomous software systems, providing tools to detect outages, investigate incidents, and optimize applications in real-time. (techcrunch.com)
Overall, Coralogix is a rapidly growing company at the forefront of observability and AI-driven insights, offering scalable and cost-effective solutions to a diverse range of clients.
Here are some notable companies and products in the AI-native observability space:
- AnoSys.AI: Provides full-stack observability for AI systems, correlating agent traces, model behavior, application telemetry, and business signals. (anosys.ai)
- Dash0: Offers OpenTelemetry-native observability with autonomous engineering agents that investigate incidents and propose fixes. (dash0.com)
- Oodle AI: Delivers an AI-native observability platform designed for full-fidelity telemetry and instant answers, emphasizing cost efficiency. (oodle.ai)
- Osuite: Provides AI-native observability with rapid instrumentation, enabling teams to find root causes and implement fixes swiftly. (osuite.io)
- Honeycomb: An observability platform built for the AI era, offering unified telemetry and AI agent integrations for rapid root cause analysis. (honeycomb.io)
- TraceHawk: Specializes in full-stack observability for AI agents, featuring span waterfalls, decision trees, cost attribution, and real-time alerts. (tracehawk.dev)
- Olly: An autonomous observability agent that provides real-time monitoring and insights, enabling prompt querying and dynamic visualizations. (ollyhq.com)
- Chronosphere: A next-generation observability platform tailored for high data-volume and AI-driven environments; acquired by Palo Alto Networks for $3.35 billion. (itpro.com)
- Dynatrace: An advanced observability platform offering AI-driven anomaly detection and root cause analysis, with recent enhancements through the acquisition of Bindplane. (techradar.com)
- Bitmovin Observability: Provides real-time insights into video playback, offering session-level monitoring and advanced error debugging tailored for video streaming. (tvtechnology.com)
In the AI-native observability space, several companies and products stand out for their innovative approaches to monitoring and managing AI-driven systems:
- TraceHawk: Specializing in AI agent observability, TraceHawk offers full-stack monitoring for AI agents, including span waterfalls, decision trees, cost attribution, and real-time alerts. It integrates seamlessly with existing tools and is OpenTelemetry-native, ensuring no vendor lock-in. (tracehawk.dev)
- OpenObserve: OpenObserve provides an AI-native observability platform that unifies infrastructure, application, and large language model (LLM) monitoring. Its Observability 3.0 capabilities include autonomous AI Site Reliability Engineering (SRE), anomaly detection, and LLM observability, enabling proactive operations. (openobserve.ai)
- Base14: Base14 offers a full-stack observability solution with a unified telemetry data lake, supporting logs, metrics, traces, and LLM data. It emphasizes full cardinality and zero sampling, ensuring comprehensive data retention and analysis. (base14.io)
- Groundcover: Groundcover has expanded its AI observability capabilities to support agentic workflows in Google Cloud environments. It provides real-time insights into LLM interactions, aiding engineering and platform teams in monitoring production environments effectively. (businesswire.com)
- Raindrop: According to DeployGraph, Raindrop is the most popular AI observability vendor among AI companies, used by organizations like Avoca, Clay, Replit, Sourcegraph, Speak, and Vercel. (deploygraph.com)
- Arize AI: Also highlighted by DeployGraph, Arize AI is utilized by companies such as DoorDash, Instacart, Pilot, Reddit, Shopify, and Twilio for AI observability. (deploygraph.com)
These companies are at the forefront of integrating observability solutions tailored for AI-driven environments, addressing the unique challenges posed by AI systems.
ChatGPT answers describe Coralogix accurately when asked by name but did not surface it unprompted in category or recommendation lists for 'AI-native observability'. The company’s product positioning can generally be trusted from the DIRECT answer, but financial and headcount claims should be verified from primary sources.
- AI outputs can vary between runs and prompts; omission from category/recommendation lists does not prove lack of market presence.
- Web-derived details about funding, valuation, HQ, and employee counts should be cross-checked against primary filings or company releases.
- The provided REAL profile did not include founders, funding, or exact headquarters, so some DIRECT claims could be recent updates not reflected here.
Risks & Red Flags
No material public risk signals found. An absence of public concerns isn’t a clean bill of health — early or private companies may simply not generate coverage.
An absence of publicly-reported concerns is not a clean bill of health: private disputes, recent events not yet reported, or coverage restricted to non-public filings may exist.
Confirmatory diligence is advised (searches of litigation/regulatory databases, customer reference checks, and a security posture review) to ensure no non-public or jurisdiction-specific issues are present.
Frequently asked questions
What does Coralogix do?
Coralogix is an AI-native observability platform and data lake that ingests, stores and queries all telemetry for unified monitoring, analysis and cost-optimized retention.
How much funding has Coralogix raised?
Coralogix has raised $550M in disclosed funding. Its most recent disclosed round was a $200M Series F in 2026, led by Advent International and Aleph.
Who are Coralogix's main competitors?
Coralogix's named competitors include Logz, Honeycomb, New Relic and Grafana.
Who founded Coralogix?
Coralogix was founded by Ariel Assaraf and Yoni Farin.
Where is Coralogix headquartered?
Coralogix is headquartered in Ramat Gan, Israel.
What market does Coralogix operate in?
Coralogix operates in the Ai native observability market (B2B). Its total addressable market is estimated at USD 10.7 billion (2033).
How does Coralogix's pricing work?
Coralogix uses a subscription pricing model.
Compiled by AlgoTurk from public web sources · . Not investment advice.