OUR STORY
We built the platform
we always knew was missing.
Parlon is an infrastructure observability company founded by three veterans with one shared conviction: the tools enterprises have been forced to work around for years were never going to be fixed from the inside.
3
Co-founders
30+
Years in observability
Cambridge
Headquarters
~70%
Reduction in alert noise with Alert Auto-Tune™
< 4 hrs
Time to first value — synthetics live same day
90 days
Typical time to fully decommission legacy stack
3–8×
Lower 3-year TCO vs. legacy monitoring platforms
THE PROBLEM
Legacy platforms were built for a world that no longer exists.
Legacy monitoring platforms were designed for static, pre-cloud infrastructure. Your network is now hybrid, containerized, and AI-driven. Their tools weren't — and their new owners aren't moving fast enough to change that.
+200-300%
Renewal Shock
Acquisitions and consolidation have changed the economics of legacy monitoring. Subscription conversions, mandatory bundles, and $1M+/yr contracts, before services.
2-5 FTE
Ops Overhead That Doesn't Scale
Administering legacy platforms requires 2–5 dedicated full-time engineers — people who should be building, not babysitting tooling.
Blind Spots
AI Workloads Are Invisible
Legacy platforms have no visibility into LLM workflows, AI inference latency, or model drift. They were never designed to observe what you're building today.
WHAT WE DO: INFRASTRUCTURE OBSERVABILITY REIMAGINED
The observability platform built for how infrastructure works today.
The infrastructure enterprises run today looks nothing like what it looked like five years ago. It's hybrid, ephemeral, container-driven, and increasingly powered by AI. But the tools most teams rely on were architected for a simpler, more static world.
Parlon is a unified infrastructure observability platform built from first principles to close that gap. A Normalization Engine structures telemetry at ingestion into a trusted data fabric. Active synthetic validation continuously tests real paths and workflows — including AI and LLM-driven systems. And Alert Auto-Tune uses learning-based intelligence to cut alert noise by approximately 70%, so teams act on signals they actually trust.
The result is a platform that doesn't just measure. It verifies, predicts, and integrates — meeting human operators and AI systems wherever they work.
- NORMALIZATION ENGINE
- ACTIVE SYNTHETIC MONITORING
- ALERT AUTO-TUNE
- LLM-AWARE SYNTHETIC MONITORING
- OPEN APIs
- SAAS | ON-PREMISE | AIR-GAPPED
Normalization before correlation
Most platforms ingest raw vendor-specific telemetry and try to make sense of it later. Parlon normalizes at ingestion — every metric, event, and path mapped into a consistent schema from day one. That structural choice makes everything downstream faster, cheaper, and more trustworthy.
Active, not passive
Legacy tools wait for something to break. Parlon continuously validates real paths, AI workflows, and critical endpoints — surfacing latency, drift, and failure modes before users feel the impact. Behavior-first, not metrics-first.
Signal over noise
Alert Auto-Tune learns system behavior over time, suppresses low-value noise, and correlates alerts into a single escalating stream. When Parlon alerts, it's worth acting on. That trust is the whole point.
Flexible by design
No lock-in. Open APIs, streaming export, vendor-agnostic collection, and flexible deployment — SaaS, on-premise, or air-gapped. Parlon is designed to work with your stack, not to own it.
WHAT WE DO
The observability platform built for how infrastructure works today.
"We watched teams drown in alerts but miss what actually mattered. We saw AI workloads surge while the data needed to observe them stayed scattered across disconnected tools. And we realized that no amount of incremental improvement was going to fix what was fundamentally an architectural problem."
The three of us spent our careers inside the infrastructure observability industry — building, selling, and deploying the tools that enterprises have been forced to work around for years.
We've built a company together before. We know this market, these customers, and these problems from the inside. And we've seen firsthand what happens when the incumbent tools can't keep pace: enterprises overpay, teams underperform, and the platforms that were supposed to create visibility end up creating complexity.
So we built a novel infrastructure observability company, Parlon. Not an incremental improvement. A different foundation entirely.
Normalization as a Core Primitive
Every metric, event, and path is mapped into a consistent schema at ingest. No custom parsers. No brittle correlation scripts. Clean data from day one — across all vendors, environments, and AI workloads.
Active, Behavior-First Observability
Parlon doesn't wait for things to break. LLM-aware synthetic tests continuously validate real paths, AI workflows, and critical endpoints — surfacing latency and drift before users feel it.
Alert Auto-Tune™
Learning-based alerting that earns trust. Alert Auto-Tune analyzes historical behavior, suppresses low-value noise, and correlates alerts into a single escalating stream. When Parlon alerts, it's worth acting on.
Low Switching Friction by Design
SaaS-first, no hardware, open APIs, streaming export. Deploy alongside your existing stack on day one. Run a 30-day proof of value. Decommission the incumbent in 90 days. Parlon is an exit ramp, not a rip-and-replace.
THE TEAM
The people building Parlon.
Three co-founders who have spent their careers inside the industry Parlon is built to transform.
Matt Goldberg
CEO + Co-founder
Software engineer turned enterprise infrastructure executive. Matt led global strategic solutions at a major network performance management company and co-founded and served as COO at an IT automation platform acquired by IBM. He built Parlon to solve the architectural problems he spent a decade watching enterprises struggle with.
Chris Rohter
CRO + Co-founder
Go-to-market leader in enterprise infrastructure and observability. Chris has led sales, marketing, and alliance functions at Akamai and across two companies he helped build that were acquired by IBM. He knows the enterprise observability buyer because he’s spent his career serving them — and listening to what the tools they had weren’t doing.
Soumo Nandi
Chief Architect + Co-founder
Infrastructure technologist with deep roots in carrier network operations. Soumo’s path ran from the Verizon Wireless Network Leadership Development Program through solutions architecture at multiple observability and DNS infrastructure companies, including two IBM acquisitions. He designed the architectural foundation that makes Parlon’s normalization-first approach possible.
WHAT WE BELIEVE
The principles behind how we build.
Not a list of wall-poster platitudes. The actual decisions that shaped Parlon's architecture and go-to-market.
Architecture over feature lists
The right foundation makes everything else possible. Normalization at ingestion isn't a feature — it's the structural decision that makes alerting, correlation, and AI trustworthy. We made that call first and built from there.
Time to value is a product decision
Months of professional services and configuration before you see anything useful isn't an implementation reality — it's a design failure. Parlon runs synthetics within hours of deployment. First value on day one is the expectation, not the exception.
No lock-in, ever
Open APIs, streaming export, vendor-agnostic collection, flexible deployment. The platform you choose for observability should make you more capable, not more dependent. We designed Parlon to consolidate, not to trap.
Signal over noise is the whole point
An observability platform that generates alerts nobody trusts has failed at its fundamental job. Alert Auto-Tune exists because we believe alerting should earn operator attention, not compete for it. When Parlon alerts, it matters.
JOIN US
Join us as we build the infrastructure observability company teams have been waiting for.
We're a small, focused team solving a problem we know deeply, because we've lived it. We're not building another feature on top of a legacy architecture. We're rethinking the foundation, and we're doing it with a group of people who care as much about the craft as the outcome.
We don't have a careers page. If you're drawn to hard infrastructure problems, care about doing things right, and want to work somewhere your contributions are visible from day one; we'd rather hear from you directly.
- Deep infrastructure expertise. You know how networks, cloud systems, and modern stacks actually behave — and you've seen what happens when observability fails.
- Bias toward building. We're a small team. Everyone ships. Everyone has opinions about the product. That's the point.
- Long-term thinkers. We're building a durable company, not chasing a quick exit. We want people who want to be here for what it becomes.
WHERE WE ARE
Cambridge, MA
We're based in Cambridge — close to MIT, Harvard, and a dense ecosystem of enterprise infrastructure talent and customers. We're a small team building something we believe is important, and we're hiring people who share that conviction.
- One Mifflin Place, Suite 400 #610, Cambridge, MA 02138
- hello@parlon.io
- parlon.io