PacketSafari

On-premises deployment · Private AI

Your infrastructure. Your boundary.

Run the same PacketSafari RCA and security workflows inside your controlled infrastructure. Packet storage, identity, retention, AI, and egress follow your deployment policy while conclusions remain inspectable.

Design your deployment Explore private AI fit

Infrastructure, model fit, concurrency, recovery, and workload capacity are confirmed for each deployment profile.

Customer deployment boundaryEgress policy · enforced
Packet storageCapture stays privateRetention · access · audit
bounded decode
PacketSafariCore EngineFrames · flows · fields
compact evidence
Qualified routeYour AI endpointPrivate · hosted · approved API

The complete operating boundary

Control more than the model.

On-premises carries the same PacketSafari evidence contract into a customer-controlled deployment. Qualify the data, identity, AI, and operational controls together.

Packet storage

Full captures and persisted investigation outcomes remain inside the customer-controlled storage boundary.

Identity and access

Connect the deployment to the approved organization identity and access policy.

Retention and audit

Apply customer lifecycle, deletion, evidence-access, and audit requirements.

AI and egress

Route bounded evidence only through an approved customer-operated endpoint and explicit egress policy.

Operations

Qualify infrastructure, updates, recovery, support, and shared operational responsibility before production.

Model + infrastructure sizing

Private-AI deployment planner.

Already own hardware? See which supported models fit. Targeting a model? Compare the reference infrastructure it requires.

Compare capacity fit, PacketSafari support status, context, concurrency headroom, and indicative infrastructure cost. Hardware prices are indicative USD purchase ranges and exclude networking, facilities, support, and PacketSafari. Fast identifies a tested route that met the focused-case target; it is not a universal latency guarantee. Final runtime, topology, and investigation quality are confirmed during deployment qualification.

Supported infrastructure profileModel fit confirmed during deployment

8× H100 · 640 GB

A supported PacketSafari enterprise infrastructure profile for customer-operated AI, with room for larger models and concurrent investigations.

Indicative hardware price$250K–$400K
Supported and evaluated model fitQualification included
  • GLM 5.34-bit context
    Supported · Evaluation

    Supported for evaluation; context and concurrency are sized for the deployment.

  • Kimi K24-bit context
    Supported · Fast

    Tested Fast option; usable context and concurrency are sized for the deployment.

  • Kimi K2.6Model-dependent context
    Supported · Fast

    Supported alternative model for a PacketSafari deployment.

  • MiniMax M3MXFP8 capacity fit context
    Not supported

    Capacity fit only; the model failed PacketSafari’s investigation-quality test.

  • DeepSeek V4 Flash 0731Quantized capacity fit context
    Supported · Fast

    Supported focused-model option; exact runtime fit is confirmed during deployment.

  • Qwen3 235BRevision-dependent context
    Not supported

    Capacity fit only.

  • Qwen3 Coder (large)Revision-dependent context
    Not supported

    Capacity fit only.

Frontier deployment comparison

Choose where frontier intelligence runs.

Compare a managed frontier route with supported and candidate private-AI options. The deployment boundary changes; PacketSafari’s packet evidence contract does not.

Managed frontier

OpenAI GPT-5.6 Sol

Position
Hosted strongest-model route
AI boundary
Approved managed provider
Infrastructure
No customer GPU cluster
Published context
1.05M tokens
Availability
SaaS and approved hosted deployments
Supported private reference

Kimi K2

Position
Recommended on-prem starting point
AI boundary
Customer-operated endpoint
Infrastructure
8× H100 (4-bit) or 8× H200 reference profiles
Published context
Up to 256K, deployment-sized
Availability
After deployment qualification
Private frontier evaluation

Kimi K3

Position
High-capacity on-prem evaluation
AI boundary
Customer-operated endpoint
Infrastructure
8× B300 or 8× AMD MI355X reference profiles
Published context
1M tokens
Availability
Not currently supported
What the number meansContext is the model’s working envelope, not the PCAP size limit.

PacketSafari keeps packet processing in the Core Engine and supplies compact, relevant evidence to the Agent. The usable context configured for a deployment may be lower than the model’s published maximum.

Shared foundationPacketSafari Core Engine

Bounded packet evidence · inspectable findings · one investigation workflow

Current model evidence

Supported means tested. Not merely listed.

Finding a model through an endpoint is only discovery. PacketSafari separates API compatibility, investigation quality, and the hardware profile that will carry the workload.

Supported · Evaluation

GLM 5.3

Deployment-sized context
Available for evaluation

OpenRouter or customer-operated inference. Use 4-bit quantization on 8× H100; qualify the exact route before production.

Supported · Fast

Kimi K2

256K tokens context
Recommended qualified option

A tested Fast option. Use 4-bit quantization on 8× H100; usable context is sized during deployment.

Supported

GLM 5.2

1M tokens context
Qualified deployment option

Available as an alternative model for qualified customer-operated deployments.

Supported · Fast

DeepSeek V4 Flash 0731

Model-dependent context
Supported

A tested focused-model option; exact endpoint compatibility is confirmed during onboarding.

Experimental

Kimi K3

1M tokens context
Not currently supported

Available only for evaluation and future deployment assessment.

Not supported

Qwen3 Coder 30B

256K native · up to 1M extended context
Not currently supported

Available only for evaluation and future deployment assessment.

Not supported

Qwen3 235B

Revision-dependent context
Not currently supported

Available only for evaluation and future deployment assessment.

One qualification boundary

Qualify once. Monitor drift without spending.

A short validation uses synthetic data only. Ongoing monitoring checks for material changes without touching a customer capture.

  1. Discover

    Confirm your selected model and deployment profile.

  2. Qualify

    Validate compatibility without using a customer PCAP.

  3. Accept

    Confirm investigation quality and operating capacity.

  4. Monitor

    Keep the approved deployment profile current.

Validated for your deployment. PacketSafari confirms the selected model, endpoint, workload, and capacity profile before production use.

Private AI deployment

Start with your captures, cluster, and security boundary.

Design your deployment Read the on-prem AI docs