[ AVAILABLE NOW / SHIPPING TO EU, US ]

Private AI infrastructure, deployed for your business.

Purpose-built hardware. Workflow-optimized models. Production-ready software. One integrated system, live in weeks.

30-minute call. No commitment. We'll assess your workload and model your costs.

nameikioma · 勢間
throughput2,400 tok/s
memory bw4.8 TB/s
paramsup to 1T
ctxup to 1M
burn-in96 h verified
THE COST OF RENTING INTELLIGENCE

Cloud AI means variable costs, data leaving your premises, and dependency on providers who can change terms overnight. For some teams, that's not a trade-off — it's a non-starter.

[ WHO WE SERVE — TEAMS THAT CAN'T OUTSOURCE TRUST ]

Banking & capital markets

MNPI · MAR · DORA

Trading desks and credit teams that handle material non-public information — where one mishandled prompt is a regulatory event.

Healthcare & life sciences

PHI · HIPAA · GxP

Hospitals, payers, and pharma running on patient records and trial data that legally cannot touch a third-party inference endpoint.

Defence & aerospace

ITAR · EAR · CMMC L3

Primes and tier-1 suppliers working under export-control regimes where 'we used a foreign API' ends contracts and clearances.

Law & professional services

PRIVILEGE · WORK PRODUCT

Firms whose business model rests on attorney-client privilege, audit confidentiality, or M&A secrecy that survives a subpoena.

Industrial R&D

TRADE SECRET · PATENT

Manufacturers, semiconductor designers, and energy firms whose process IP is a decade of competitive advantage they refuse to upload.

Public sector & critical infra

NIS2 · NERC CIP · OFFICIAL

Agencies, utilities, and operators of essential services where data residency is statute, not preference — and uptime is sovereign.

If your data can't leave the building, your inference shouldn't either. That's where we come in.

01 · the solved stack

Three layers, designed for each other.

Hardware, models, and software shipped as one integrated system — so your team uses it instead of maintaining it.

01 HARDWARE ▸

Purpose-selected silicon, burned in by us.

Hardware specified to your workload, not your guess at it. 96-hour burn-in before it leaves the floor; a serial, a calibration sheet, and a name etched on the chassis.

  • Hardware matched to your actual workload
  • Pre-validated configurations, tested before delivery
  • Setup, integration, and burn-in handled by us
  • On-premises — your hardware, your premises
SILICON · IKM-1spec sheet / rev.03
1U · FRONT
IKM-1ASIC · 4 nm · 96 GB HBM3e
THERMALpassive air · 312 W
CHASSIS1U · 19" · OCP
throughput 2,400 tok/s memory bw 4.8 TB/s burn-in 96 h MTBF 200k h
02 MODELS ▸

Open weights, tuned to your workflows.

Foundation model post-trained on the categories of work your team actually does. We benchmark against your task suite, not generic leaderboards — and the weights are yours, perpetually.

  • Open-weight models, selected for your tasks
  • Fine-tuned on your task suite
  • You control the weights — always
MODEL · ikioma-32B / v4attention · 64 heads
layer ↓
heads →low → high
01 base — open weights 02 your tasks — domain SFT 03 benchmarked — against suite 04 deployed — your weights
params 32.4 B · 4-bit context 128k tool head 14 actions licence perpetual
03 SOFTWARE ▸

Production-ready, day one.

OpenAI- and Anthropic-compatible API surface, so your existing integrations work unchanged. Sandboxed tool execution, signed audit log, single-binary deploy. Your team uses it. We maintain it.

  • OpenAI / Anthropic API compat
  • Sandboxed tool exec · MCP
  • Signed, tamper-evident audit log
RUNTIME · Conduit / 1.4single binary · self-hosted
POST /v1/chat/completions → ikm-rack-01.local
{
  "model": "ikioma-32B",
  "messages": [/* ... */],
  "tools": ["fs", "erp", "sql"]
}
200 · 41 ms · signed sha256:9c12…b4a7
audit · last 4 events
14:02:11tool.fs.read
14:02:11tool.erp.query
14:02:12model.emit
14:02:13policy.deny×
sandbox · 14 tools
fs sql erp git sh mail tkt cal www img vc +3
API surface OpenAI / Anthropic compat deploy single binary

You don't need to figure this out yourself. We already have.

02 · vs the alternatives

The middle path — independence without the engineering overhead.

You've already decided you want private AI. The remaining question is whether to build it yourself.

OPT.A Cloud AI OPT.B DIY private AI OPT.C ikioma ↓ best fit
Data location ×Third-party servers Your premises Your premises
Time to deploy ~Immediate, but dependent ×6–12 mo weeks
Expertise required ~API integration ×ML eng + DevOps team None
Cost model ×Variable · per-token ~High capex + maintenance Fixed · predictable
Ongoing risk ×Vendor dependency ×Entirely on your team Supported + updated
Rate limits ×Yes No No
Model control ×None ~Full, but complex Full, managed for you
Comparison reflects typical mid-market deployments. On the deployment call, we'll model your specific workload against each option.
03 · how it works

Four steps. Mostly ours.

The path is finite, the timeline is short, and you don't carry the engineering load.

01
DEPLOYMENT CALL · 30 MIN

We learn your workload.

Your data requirements, team capabilities, integration surface. We come prepared; you walk away with a costed scenario.

02
SOLUTION DESIGN · ~1 WEEK

We design the system.

Hardware specified, model fine-tuned for your tasks, software stack configured against your existing systems. You approve the spec sheet.

03
DEPLOYMENT · 2–4 WEEKS

We install on your floor.

Appliance arrives, racks, burns in, tests against your acceptance suite. Your team is in the room — knowledge transfer happens at install.

04
LIVE · ONGOING

You run it. We back it.

Your team uses AI on your terms. We handle model updates, security patches, and performance tuning under a named-engineer SLA.

Start with step 1 → first call · zero commitment
04 · the work behind the box

We built what we couldn't find.

Since 2023, we've worked with models from every major provider, tested hardware from prosumer to cloud-grade, and shipped AI-powered products in production. The hardest part of private inference isn't the technology — it's the logistics of assembling it into something that just works. ikioma exists to remove that barrier entirely.

Every major model provider
evaluated in real production workloads
Hardware from consumer devices to cloud servers
tested across the full range
AI-powered products
shipping to real users
Founded
to make private inference straightforward
FOUNDING TEAM · HELSINKI

Founded by a team with backgrounds in software development and information security. We ship AI-powered products daily — ikioma grew out of our own need for private inference that doesn't require becoming an infrastructure team.

team 2 · Helsinki, Finland est. 2026 backgrounds software dev, infosec
05 · objections, answered

Things people ask before the call.

Modern open-weight models match cloud API performance on the categories of work most businesses care about — document understanding, summarisation, classification, structured extraction, code, agentic tool use. We benchmark against your specific workloads during the deployment call. You see the numbers before any commitment.

We handle it. Model updates, software patches, performance tuning — ongoing support is included for the warranty period. A named engineer owns your account; updates are signed and reversible. You always know what changed and why.

Your system isn't locked to a single model. Swap models, scale out with additional appliances, or retune for new tasks as workloads evolve. You own the hardware; we help you get the most from it. Trade-in credit applies if you upgrade to next-gen silicon.

Private inference is a capital asset, not a subscription line. Most customers break even versus equivalent cloud spend within 4–7 months on typical agentic workloads. On the deployment call, we'll model your specific token volume, response-time targets, and compliance requirements — you'll see the crossover month for your numbers, not ours.

NEW · HOSTED, FLAT-RATE INFERENCE

Not ready to rack hardware? Rent the model, not the meter.

For teams running coding agents and autonomous workflows who want private inference today — without the on-prem build. Unlimited inference for a flat monthly fee, hosted in Finland and tuned for the agentic loop.

  • One flat €995/month VAT 0% — no per-token metering, no overage invoices
  • EU data residency · hosted entirely in Finland · never trained on your data
  • Tuned for tool-use, long-horizon tasks and coding loops
Explore the offer → join the waitlist · launching soon
statement · this month node · fi-hel-01
tokens consumed 1,482,910,544
metered equivalent €6,920
per-token charges €0.00
overage · surprises none
amount due
€995.00 /mo · VAT 0%
flat · locked
[ TAKING BRIEFINGS · TUE / WED / THU ]

/Your AI.
/Your data.
/Your infrastructure.

Every month on cloud AI is another month of variable costs, data exposure, and dependency. See what private inference looks like for your workload.

30-minute call. No commitment. We'll model your specific workload and costs.