NalaOps by Induna
NalaOps is a network operations intelligence platform for enterprise fleets. It does not reason from documentation or vendor templates. It reasons from a corpus of configurations that have already held in production - collected, analysed, and promoted only after they prove themselves on real hardware.
A configuration does not enter the corpus because it deployed successfully. It enters because it ran clean for thirty consecutive days on that exact model and firmware train. One fault resets the clock. Illustrative sequence - not live customer telemetry.
The platform
Collection, analysis, and reasoning are separate systems with separate jobs. Each one hands the next a verified artefact rather than a guess.
Collection agent
Analysis & generation agent
Network Engineering Reasoning & Outcomes
NalaOps flags, explains, and generates. It never pushes a change to a live network device. Every remediation and every generated design is reviewed by an engineer before a single command runs, and higher blast-radius changes - routing protocol selection, new security feature placement - require documented engineer rationale at approval, not just a click.
This is a design decision, not a limitation we intend to remove. The approval step is where engineering judgement gets built, and it is the reason the corpus is trustworthy in the first place.
Config-only tools check one question. NalaOps checks both, because a device can pass the first and still fail the customer.
Tier one
Running config captured and compared against the Golden Config for that model and firmware version. Drift and gaps surfaced in structured form.
Tier two
Operational and physical verification - CPU and memory state, boot-window log review, and per-port PoE delivery. This catches firmware-level failures where an access point draws zero power at a port that reads perfectly clean on paper.
Why NalaOps
The language model NalaOps generates with is swappable, and we expect to swap it. What cannot be swapped, licensed, or bought is the record of what has actually held in production across a real fleet - accumulated one clean day at a time.
| Dimension | A model wrapped around telemetry | NalaOps |
|---|---|---|
| Source of truth | Vendor documentation and public configuration examples. | Configurations observed running clean in production on this device model and firmware. |
| Firmware handling | A config is a config. Firmware is metadata. | Golden Configs and validated defaults are tracked per model and per firmware train, because identical syntax behaves differently across them. |
| Entry into the knowledge base | Immediately, on ingestion. | Only after 30 consecutive clean days in production. A single fault resets the clock. |
| Confidence | Fluency, presented as certainty. | A score derived from how many comparable validated deployments support the proposal - with those deployments shown. |
| Defensibility | Reproducible by anyone with the same API key. | Compounds only with production exposure and time. It cannot be shortcut with capital. |
Deployment success is the weakest possible evidence. Configurations fail days later, under load, after a reload, or when a firmware bug surfaces on a port nobody was watching. The 30-day promotion clock exists so that the corpus records stability rather than optimism - and Day-1 verification decides whether a device is even eligible to start the clock.
For investors
Every dollar raised against a narrative costs more equity than one raised against a demonstrated flywheel. The sequence below funds the highest-risk research with non-dilutive capital first, converts existing relationships into revenue second, and only then raises growth capital.
Firmware-conditional semantics, grammar-constrained generation, and calibrated retrieval similarity are research problems, not engineering tickets. They are funded through federal research channels rather than equity.
Revenue from a production deployment is a stronger input to a valuation than any projection built on it. Conversion happens on our timeline, ahead of external pressure on the customer's side.
Corpus growth rate, promotion rate, and design-partner outcomes are the metrics the round is priced on - shown, not forecast.
DevNet, then SolutionsPlus, then Cisco Investments. Each stage earns the credibility and relationship depth the next one requires. Skipping a stage wastes the introduction.
PRE-PUBLICATION - No funding programme, award status, design partner, or customer is named or implied anywhere on this site. Nothing here claims an award, a signed contract, or a named relationship. Add these back only once disclosure clearance is explicit.
For network teams
The senior network engineer shortage is not solved by automating away the work junior engineers learn from. NalaOps is built so that every explanation it produces is also a teaching artefact.
Next step
Tell us what your fleet looks like and what is currently unverifiable about it. An engineer reads every request and replies.