CodiLime
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Capability

AIOps & GenAI

CodiLime builds custom AI/ML systems for network and infrastructure operations. We deliver them end to end, or engineer them into the products you ship and the platforms you run. Both are built on your telemetry, your topology, and your tools. We’ve spent 15 years building network software for the vendors whose gear you run. That’s why our models reason on the right signals and our automations act predictably in production.

Measured impact

What we deliver

How we do it

We build the stack from the bottom up. Automation you can rely on and telemetry you can trust come first. Then classic ML turns that data into signal, GenAI reasons over it, and agents come last — acting through automation workflows that are already proven reliable.

  1. Telemetry

    The whole estate, normalized

    metrics, logs, traces & flows · topology · configuration & device state · incident history

  2. Classic ML & statistics

    Turns raw telemetry into trusted signal

    anomaly detection · event correlation · clustering · forecasting

  3. GenAI reasoning

    Reasons over trusted signal

    investigation orchestration · ranked root-cause hypotheses · evidence summaries · natural-language interaction

  4. Agentic action

    Decides, then acts through automation

    policy-gated remediation · human approval · verification & rollback · full audit trail

  5. Automation & orchestration

    Every action runs through here

    API-driven configuration · runbooks as code · intent-based provisioning · closed-loop workflows

Technology

  • Models & orchestration

    • LangChain
    • LangGraph
    • MCP
    • PyTorch
    • ONNX
    • Self-hosted LLMs

  • Telemetry & observability

    • Prometheus
    • Grafana
    • Grafana Loki
    • Splunk
    • InfluxDB

  • Forecasting & ML

    • Prophet
    • Holt-Winters
    • ARIMA
    • LSTM

  • Infrastructure & acceleration

    • Kubernetes
    • CUDA
    • NVIDIA GPU
    • NVIDIA BlueField DPU
    • GPUDirect RDMA
    • DPDK
    • VPP
    • SmartNIC
    • FPGA

Proof of capability

Solutions we’ve built for network and infrastructure operations, with measured results. Watch the demo or read the case.

Why CodiLime

  • Network & infrastructure expertise

    We know the protocols, architectures, and telemetry behind the model, and the operational constraints a real NOC, SRE, or SecOps team works under. That’s the context we build AI for.

  • Software & product engineering

    An agentic system is a hard software problem. Keeping one predictable as it grows takes real engineering discipline — architecture, testing, observability, release process. We’ve spent years shipping production products for data centers, telecoms, and enterprises.

  • Classic ML and GenAI together

    We use statistical models and classic ML to produce trusted signals first, then let an LLM or agent reason over them. We were doing ML for networks long before ChatGPT.

  • Automation & orchestration experts

    We deliver automation and orchestration as practices in their own right. That means we build the execution layer ourselves, then put agents on top of it: one team, one architecture.

  • Security & guardrails

    We build in identity, access control, guardrails, and end-to-end auditing from day one, the same discipline as our Security practice. AI that can act on your network runs inside explicit policy, with every action attributable.

Insights

FAQ

Good to know

  • What is AIOps for networks and infrastructure?

    AIOps applies AI/ML to network and IT operations, using anomaly detection, event correlation, and automated root-cause analysis to turn floods of alerts, metrics, logs, traces, and flows into a short list of actionable incidents. CodiLime builds it specifically for network and infrastructure operations, combining classic ML, GenAI, and automation into one production workflow.

  • How is this different from running an LLM or ChatGPT over our logs?

    CodiLime runs classic ML over your telemetry first to correlate, cluster, and forecast, so the model reasons over clean, structured signal. Every action it can take then runs through policy guardrails, with human approval, verification, and a full audit trail.

  • Who is CodiLime’s AIOps for?

    Telcos, ISPs, network and infrastructure vendors, NOC and SRE teams, and enterprises running complex networks — anyone drowning in operational data and manual investigation.

  • What results can AIOps realistically deliver?

    Typical results after tuning are 60–85% less alert noise, and a common target is 30–50% faster mean time to resolution; both depend on data quality and process maturity. In a netflow project for a major Asian telecommunications provider, 60% of the IP addresses our model flagged were confirmed malicious in VirusTotal within a week.

  • Will an AI agent make changes to my network?

    Only the changes you authorize. Every action an agent can take runs through policy-gated automation with human approval by default, plus verification, rollback, and an end-to-end audit trail of what ran and who approved it. CodiLime enforces identity, access control, and secrets with Keycloak, OPA, and OpenBao, and scopes an agent’s tools by role, so it reaches only the devices and commands that role allows.

  • Can it run on-prem or air-gapped?

    Yes. CodiLime deploys AIOps to cloud, on-prem, or the edge — including self-hosted LLMs and inline inference on SmartNIC, DPU, or FPGA — and your data can stay on your infrastructure.

  • Do you sell a product or build it for us?

    CodiLime builds it for you. Every AIOps system is custom: we deliver it end to end, or engineer it into the products you ship and the platforms you run. It runs on your telemetry, your topology, and your tools, and stays vendor-neutral, integrating what you already own.

  • What does it take to run AIOps in production?

    Ingestion pipelines, integrations with your ticketing and ChatOps, deployment, monitoring, and a retraining loop that keeps accuracy from drifting as the network changes. CodiLime builds all of that, then hands over the code and the operational know-how so your team can run it.

  • What do you need from us to get started?

    One workflow worth fixing — a noisy alert stream, a slow investigation, or a capacity decision you’re making blind — and access to whatever telemetry you already collect. Where the telemetry isn’t there yet, CodiLime builds it: observability is a practice of ours in its own right, and early work often includes tightening what you collect. From there we assess the data and scope a path from pilot to production.

Put AI into the operations loop

Bring us a high-noise operational workflow, a difficult investigation process, or a forecasting problem. We’ll assess the data, identify where AI adds value, and define a path from pilot to production.