Open models, engineered into the enterprise.

Tekindx embeds senior engineers inside your organisation to evaluate, fine-tune and run open-weight LLMs on infrastructure you control. You get production systems in weeks, and you own the weights, the data and the roadmap.

Open-weight leaderboard

Artificial Analysis Intelligence Index, independent benchmark, retrieved 24 Oct 2026

ModelIntelligence indexSpeed$ / 1M tokens
MiMo-V2.6-ProXiaomi
46
52 t/s$0.20
DeepSeek V4.1 FlashDeepSeek
45
198 t/s$0.20
GLM-5.3Z AI
45
85 t/s$0.90
Step 5 PreviewStepFun
44
220 t/s$0.50
Muse Spark OpenMeta
39
151 t/s$0.80
Qwen3.8 27BAlibaba
34
45 t/s$0.50
InklingThinking Machines
25
145 t/s$0.70
Top closed model: Claude Opus 5.5, 58Source: Artificial Analysis. Refreshed weekly. Public benchmarks pick the shortlist; your evaluation set picks the model.

Open-weight models we evaluate and deploy

  • MistralMistral AI, France
  • QwenAlibaba, China
  • DeepSeekDeepSeek, China
  • KimiMoonshot AI, China
  • GLMZhipu AI, China
  • MiniMaxMiniMax, China
  • InklingThinking Machines, US
  • LlamaMeta, US
  • GemmaGoogle, US
  • HunyuanTencent, China
  • StepStepFun, China
  • BaichuanBaichuan, China

Serving stack

  • vLLM
  • NVIDIA
  • AMD Instinct
  • Hugging Face
  • SGLang
  • Kubernetes

The engineer who scopes it ships it.

Three senior engineers work inside your team from first workshop to handover. No model is chosen until it has been tested on your data.

  1. 01 Embed Weeks 1–2

    One evaluation set.
    Built from real work.

    Operator interviews

    “Anything over 50k goes to a second reviewer.”

    Process documents

    Approval depends on amount and region.

    System exports

    Resolved tickets, with the answer that was sent.

    240 cases

    Evaluation set

    3 workstreams, signed off by your team

    • C-001Extract totals from supplier invoices
    • C-002Classify the intent of a support ticket
    • C-003Draft a reply in policy language
    Signed-off cases 0 / 240
    • Extraction96
    • Classification78
    • Drafting41
    • 2 more workstreams25
  2. 02 Evaluate Weeks 2–3

    Several open models.
    One honest scorecard.

    Open-weight candidates

    Same prompts, same cases, same hardware.

    Closed baseline

    The API you would otherwise pay for.

    Your constraints

    “Under 800 ms, on the two GPUs we have.”

    6 models

    Model recommendation

    Scored on all 240 cases

    • M-01Accuracy against the baseline
    • M-02Latency at the 95th percentile
    • M-03Cost per thousand requests
    Scorecard 6 / 6 run
    • Beat the baseline3
    • Met the latency limit4
    • Under budget5
    • Recommended1
  3. 03 Adapt and ship Weeks 3–12

    Weekly releases.
    On your GPUs.

    Fine-tuning data

    Adapters trained on outputs your team corrected.

    Retrieval

    Policies and precedents, cited in every answer.

    Guardrails

    Answer, escalate or refuse, by rule.

    Week 8 of 12

    Release v0.7

    Adapter v3, citations required, rollback tested

    • R-071Promote adapter v3 to production
    • R-072Require a citation on every answer
    • R-073Rehearse rollback to v0.6
    In production 1,200 / day
    • Accepted without edit71%
    • Escalated to a person9%
    • p95 latency640 ms
    • Rollbacks0
  4. 04 Hand over Final weeks

    Your repo. Your runbooks.
    Your next model.

    Evals in CI

    Every change re-scored before it merges.

    Runbooks

    Monitor, roll back, upgrade.

    Pairing

    Your engineers swap in next quarter’s model themselves.

    Complete

    Handover pack

    Everything in your repositories

    • H-01Weights and adapters
    • H-02Evaluation set and CI job
    • H-03Infrastructure as code and runbooks
    Owned by you 100%
    • Weights✓
    • Evals✓
    • Serving infra✓
    • Runbooks✓

Agents that act inside your systems, under your approval.

Agents on open-weight models that read your systems, decide and write back. Dry run first, a person approves anything risky, and every step is traced.

05 Agentic workflows On your infrastructure

Every step traced.
Nothing written without a rule or a person.

Trigger

Supplier invoice arrives, no purchase order attached.

Tools

Search the ERP, read the contract, propose a posting.

Policy

Auto-post under 10k. A person approves anything above.

Run 4,812 · 6.2 s

Agent run

Invoice INV-20931, 14,200 · model: open weights, your GPUs

  • 01find_purchase_order(supplier, amount) → 1 matchdone
  • 02read_contract(PO-5571) → payment terms 30 daysdone
  • 03propose_posting(GL 6120, cost centre DXB-OPS)done
  • 04amount > 10k → hold for approvalawaiting approval
This week 3,400 runs
  • Completed by rule82%
  • Approved by a person14%
  • Refused or escalated4%
  • Writes without a trace0
Document intake

Reads, extracts, files.

Invoices, KYC packs, claims. Extracts fields against your schema, checks them against your records and files the result, with a confidence score and a link back to the source page.

Reads
Email, scans, portals
Writes
ERP, DMS, case system
Approval
Below threshold: auto. Above: a person
Service resolution

Resolves the ticket, not just the reply.

Looks up the account, applies policy, takes the action (refund, re-issue, reschedule) and writes the note. Hands over to a person with the full context when it can't.

Reads
CRM, order history, policies
Writes
Ticketing, billing
Approval
Per action type, set by you
Back-office operations

Closes the loop in your ERP.

Reconciliations, PO matching, month-end exceptions. Runs on a schedule, proposes the journal, and posts only what your rules allow. Everything else lands in an approval queue.

Reads
ERP, bank files, contracts
Writes
Journals, approvals queue
Approval
Dry run first, then by amount

When the model is yours, so is the cost curve.

On public benchmarks the best open-weight models trail the closed frontier by a margin that narrows every quarter, at a fraction of the price. On a single workflow, with fine-tuning on your own data, that gap usually closes. What changes is who controls the data, the cost and the upgrade path.

FactorOpen weights, run by youClosed API
DataStays in your cloud, data centre or sovereign regionLeaves your boundary for the provider's servers
Cost at scaleFixed GPU cost that falls per request at sustained volume; we show you the break-even before you commitPer-token pricing that rises with usage
CustomisationFine-tune on your data and keep the weightsPrompting, plus limited tuning on the provider's terms
Model choiceSwap between Mistral, Qwen, DeepSeek, Inkling and others as they improveOne vendor's roadmap
ContinuityThe version you validated keeps running until you change itModels deprecated on the provider's schedule, often with months of notice

Built for security review from the first week.

We deploy wherever your risk team needs the model to live, and we document every control so procurement and audit have what they need.

Your private cloud

Inside your own VPC on AWS, Azure, Google Cloud or a sovereign cloud region. No traffic to model vendors.

Fits most regulated enterprises

Your data centre

On your own NVIDIA or AMD GPU clusters, integrated with existing identity, logging and change control.

Fits banks, telcos and healthcare

Air-gapped

Fully disconnected environments, with weights transferred and verified through your approved media process.

Fits defence and critical infrastructure

  • Model provenanceChecksums and source records for every weight file deployed
  • Data handlingTraining and eval data never leaves your environment
  • Access controlIntegrated with your SSO and role model, least privilege by default
  • Audit loggingPrompts and responses logged to your SIEM, with PII redaction and retention set by your policy
  • Red-team evalsPrompt-injection, jailbreak, data-leakage and bias tests run before each release
  • Origin screeningModel choices checked against your policy on model origin and licence
  • Agent approval gatesAgents run read-only first; writes above a threshold wait for a named person
  • Agent trace and rollbackEvery tool call stored in your environment, replayable, and each write reversible
  • Agent limitsSteps, tokens and tool permissions capped per run and per agent

Two ways to work with us.

Every engagement starts with a fixed-price working session, so you know the scope and the price before you commit.

Enterprises and government

Private AI on infrastructure you control.

For organisations that can't send sensitive data to a third-party API but need AI in production this year.

  • Working session and evaluation set
  • Model bake-off with a written recommendation
  • 8 to 16 week build on your GPUs, then full handover
Scope a workflow

GPU clouds, model labs and integrators

Forward deployed capacity for your customers.

For partners whose customers stall between pilot and production and need senior engineers to get them there.

  • Pods deployed under your brand or ours
  • Customers reach production instead of stalling at pilot
  • More GPU hours and model usage per account
Discuss a partnership

What stays with you when we leave.

Everything lives in your repositories from day one. When a better model ships, your team can test it and swap it in.

  • Evaluation setReal cases with expected outputs your team approved
  • Model cardWhich model and size, why, and how it scored against the alternatives
  • Fine-tuned weightsAdapters plus the data and config that produced them
  • Serving codeInfrastructure as code for inference, sized to your traffic
  • RunbooksHow to monitor, roll back and upgrade

Start with a discovery call.

Our AI discovery assistant asks about your workflow, data and timeline, so the engineers you meet next already understand the problem. It takes about 10 minutes, in your browser or by phone.

  1. 1Your details
  2. 2Verify email
  3. 3Discovery call
We use your details only to prepare for the call.

Prefer email? Write to hello@tekindx.com.

Bring us one workflow. We'll put an open model behind it.

Start with a 10-minute discovery call with our AI assistant. If there's a fit, it books you straight into an engineer's calendar.

Start a discovery call