How long does it take to set up?

Initial setup, including connecting Jira, your messaging tool, and GitHub, takes a few hours. Encoding your team's flash procedure as a Sagy Skill typically takes a couple of working sessions with our team.

Does Sagy work with our existing tools?

Yes. Sagy integrates with Jira, GitHub, Slack, Microsoft Teams, and the most common artifact storage systems. The agent runs locally on the engineer's laptop and connects to your devices through serial or SSH.

Can we deploy on-premise?

Yes. We support on-premise and self-hosted deployments for teams with privacy or compliance requirements. This is increasingly common in our customer base.

What if our hardware uses a chipset or protocol you haven't listed?

The list above is what the agent knows out of the box. Sagy is designed to learn new domains quickly through your team's tickets, code, and historical context. If your stack isn't listed, talk to us, we'll tell you honestly whether the agent is ready for your context.

Do you replace our engineers?

No. The agent absorbs the repetitive, operational work around debugging, reproduction, context recovery, setup, documentation. The actual engineering judgment stays with your team. That is the design.

Available now · Wireless & Networking

The AI agent for wireless and networking device teams.

Built by engineers who spent 18 years debugging the same devices you're building. Sagy's wireless networking agent already understands the protocols, the chipsets, the SDKs, and the failure modes. Then it learns your team.

See what it already knows

The problem

The work isn't hard. It's unrelenting.

If you build wireless devices, you already know where the time goes. A customer reports a bug. Before any real debugging starts, an engineer spends hours, sometimes days, recovering context, identifying the firmware version, flashing the right image, configuring the device, attempting reproduction, retrying configurations, searching old conversations for similar incidents.

The work isn't hard. It's repetitive, mechanical, and unrelenting. And it doesn't scale. Sagy's wireless networking agent is built to absorb this work, patiently, consistently, across every ticket.

Preloaded domain knowledge

Not knowledge it has to discover. The starting point.

Out of the box, the wireless networking agent is preloaded with deep domain knowledge that generic AI tools simply do not have.

Wireless protocols

802.11a/b/g/n/ac (WiFi 5), 802.11ax (WiFi 6/6E), 802.11be (WiFi 7)
Bluetooth Classic and BLE, mesh, GATT, pairing flows
Zigbee 3.0 and Thread
Z-Wave
Matter (CSA)
Cellular, LTE, 5G NR, NB-IoT, LTE-M
LoRa / LoRaWAN
DECT-2020 NR

Networking stacks & protocols

802.1X authentication, WPA2/WPA3, EAP variants
802.11k/v/r, roaming and band steering
DFS, regulatory domain handling, channel selection
DHCP, IPv4/IPv6 dual stack, SLAAC, DHCPv6
DNS, mDNS/Bonjour, DNS-SD
TR-069 / TR-369 (USP) device management
hostapd, wpa_supplicant, nl80211, mac80211
Mesh, 802.11s, EasyMesh, vendor mesh

Chipset families & SDKs

Broadcom (BCM43xx/47xx), wl driver, NVRAM conventions
Qualcomm (QCA, IPQ), QSDK, driver internals
MediaTek (MT76xx/79xx), OpenWrt mt76 driver
Realtek wireless chipsets
Espressif (ESP32, ESP8266), ESP-IDF, WiFi/BT coexistence
Nordic (nRF52/53), nRF Connect SDK, Zephyr
Silicon Labs, EmberZNet, Bluetooth Mesh SDK

Firmware platforms & OSes

OpenWrt, package layout, build system, config patterns
prplOS, RDK-B
Yocto Project, Buildroot
FreeRTOS, Zephyr, ThreadX
Custom vendor Linux distributions

Common failure patterns

Association and authentication failures across security modes
Roaming and handover issues in multi-AP environments
Channel selection and DFS event handling
Regulatory domain misconfigurations
Bluetooth pairing/bonding failures, BLE connection drops
Mesh synchronization failures after topology changes
Cellular registration and bearer setup issues
Memory leaks, watchdog resets, long-running stability issues
WiFi/Bluetooth coexistence on shared radios

What it does for your team

Runs locally. Connects to the real device.

The agent runs on the engineer's laptop and connects directly to the device through serial, SSH, or your existing test harness.

Reproduces customer-reported bugs

Reads the Jira ticket, recovers prior context from your messaging tool, GitHub, and Jira history, identifies the exact firmware version, flashes the device, runs the reproduction steps, and retries across known wireless failure patterns, then delivers a structured report with logs and a first hypothesis.

Investigates field incidents

Pulls together everything relevant to an incoming complaint, recent firmware changes touching the wireless stack, similar past tickets, related conversations across the team, suspect commits, before the engineer opens a single tab.

Validates builds against regressions

When a new build is ready, the agent runs a pre-configured suite of reproduction workflows against your library of historical bugs, catching regressions in known failure modes before they reach QA.

Documents tribal knowledge automatically

Every investigation becomes part of Sagy's memory. The first time a senior engineer solves a tricky DFS issue, the next engineer to hit it sees the prior investigation immediately, with the full trace, logs, and resolution.

How it learns your team

The domain knowledge is the start. Your team is the value.

Your flash procedure

Encoded as a Sagy Skill once, then run consistently on every investigation.

Your build artifact storage

The agent matches firmware versions against your internal storage, with your naming conventions.

Your reproduction conventions

The way your team brings up interfaces, configures test environments, and captures logs. The agent runs your procedure, not a generic one.

Your historical incidents

Every ticket, investigation, Slack thread, and Teams conversation becomes part of the agent's memory. The more your team uses Sagy, the faster it recognizes patterns specific to your hardware.

Your codebase

The agent knows your repos, your branch conventions, and which commits to suspect when a wireless regression appears.

Who this is for

Built for teams shipping wireless or networking devices.

If your engineers spend a meaningful chunk of their week on bug reproduction, context recovery, or repetitive firmware investigation work, this agent is built for you.

WiFi router & access point manufacturersMesh networking system vendorsSmart home hub & gateway makersIoT device manufacturers (Bluetooth, Zigbee, Matter, Thread)Cellular IoT & industrial connectivity vendorsNetworking equipment OEMs and ODMsTelecom CPE & gateway providersTest & measurement vendors in wireless

Why us

Built by engineers who lived this problem.

18 years debugging wireless devices, watching the same patterns play out across team after team, company after company. The wireless networking agent isn't a generic AI tool with a marketing skin, it's a domain-specific agent shaped by years of real work, and it ships with that experience preloaded.

We're working with a small number of design partners to push this further. If you build wireless devices for a living and the work described on this page sounds painfully familiar, we should talk.

Design partner program

Talk to us about becoming a design partner.

We're deliberately taking on a small number of teams to make sure each one gets a deeply tailored agent.

w.golli@sagy.ai

Frequently asked

Questions, answered.