We turn complex problems into working intelligent systems.

Complex problems rarely need more AI.They need the right system.

RAUNEM combines deterministic logic, AI reasoning, automation and human control into systems built for real operations — not just demos.

Discuss a problemSee what we build

03 / Systems in Practice

Real systems,at their real status.

Each began as a business problem. What is built stays separate from the pattern that may carry over to yours — a pattern, not a result delivered for another field.

The problem

  1. First

    A firm needs a credible public presence — to be found.

  2. Later

    What it publishes has to scale without losing control.

Seen in practice

Fintehplus

A small accounting-services firm. One client relationship, two separate systems.

Built · verified

Web Platform

Public operating artifact

  • A public B2B platform of 75+ public pages — services, industries, solutions and articles — built to support commercial discovery and enquiries.Live today

Not operated by the marketing system.

Autonomous Marketing System

In active developmentPublishing live on selected channels

  • Keeps durable state, approval history and receipts across publication work.Operating core
  • Controlled public publishing is proven on Telegram and MAX; website/RSS/VK delivery is active.Live today
  • External outcomes are recorded and reconciled instead of being treated as automatically successful.
Latest verified milestone
Controlled public publishing across selected live channels

Stays humanHuman approval remains authoritative for consequential publication decisions.

Still evolvingThe full response → conversation → qualification → business outcome → learning loop remains in development.

Explore case study

Transferable pattern

Governed outbound communication

Controlled external actions

May fit you if…

  • Your business repeatedly produces or sends material to outside platforms.
  • A duplicate, a wrong action or a missing approval has a real cost.
  • You want human sign-off without a person doing all the work.

Probably not if…

You send only a few posts a month — buy a scheduler.

The problem

  1. Many opportunities arrive. Few deserve attention — and a wrong “yes” costs time.

Seen in practice

RAUNEM BizDev

RAUNEM’s own business-development system.

Built · verified

RAUNEM BizDev

In active development

  • Rules qualify and rank the cases before any model reasons about them.
  • A live outbound path has been verified without duplicate sending.
  • The workflow keeps its state durably, and outcomes can be traced back to what was sent — checked outside live operation.

Stays humanA person approves before anything is sent. The final decision stays with a person.

Still evolvingLive reply and outcome handling, and unattended operation.

Transferable pattern

Triage with a human decision

Qualification with bounded AI judgment

May fit you if…

  • Many incoming items compete for attention.
  • Your criteria are partly explicit rules and partly judgment.
  • A wrong “yes” costs time or money.

Probably not if…

The volume is small enough for a person to read everything.

FoundationRAUNEM uses its own internal infrastructure to place workloads deliberately across plain code, local or specialised models, and larger reasoning models, with persistent state where required.

04 / Judgment

AI is not the first thingthat acts.

Deterministic rules qualify first. AI reasons only over meaningful cases. Consequential action remains under human control.

Incoming records

  1. OP-014Inbound signalDuplicate record
  2. OP-026Market scanOutside profile
  3. OP-021Inbound signal
  4. OP-033ReferralEvidence missing
  5. OP-018Market scanPast deadline

Rules act first

OP-021Allowed context
Source
Inbound signal
Profile fit
Strong
Evidence
Verified source · required context present
Reasoning

Model not called

Evidence aligned

Profile match strong

Remaining ambiguity

Checked against rules

Human decision

Awaiting human decision

Illustrative records · reconstruction of the judgment logic, not live data

Grounded inRAUNEM BizDev — active internal system.

05 / Reliable Execution

Attempted is not done.Done has a receipt.

After the system decides to act, it keeps the state of the work, asks a human before consequential external action, and counts the receipt — not the attempt — as evidence. When the outcome is uncertain, it reconciles instead of retrying blind.

Work item · illustrative

RUN-042

Current state

ReadyApprovedAttempted — not completeOutcome unknownReconcilingComplete · verified
  1. StateValidated against the publishing rulesReady
  2. ApprovalA human approves the external actionApproved
  3. ActionPublish request sent to the platformAttempted
  4. UncertainNo acknowledgement received. Outcome unknown.Not retried — it may already have happened.Unconfirmed
  5. ReconcileExternal record checked, read-onlyChecked
  6. ReceiptAcknowledgement matches the requestConfirmed

Illustrative work item · reconstruction of the reliability logic, not live data

Grounded inFintehplus AMS — active development.

06 / Owned System

What lasts in an AI systemis not the model.

Your rules, state, integrations, evaluation and history are specific to your business. They stay under your control. Models and runtimes are dependencies, placed by workload.

Workload A

Rule check

  • Exact answer
  • Cost-sensitive

No model

Exact logic: rules, validation, state transitions

Rule checkRuns as plain code · no model

Workload B

Client brief

  • Sensitive context
  • Moderate reasoning

Specialised model

Task-specific inference · local where required

Client briefRuns on a specialised model

Workload C

Open-ended analysis

  • Heavy reasoning
  • Latency-tolerant

Frontier reasoning

External model, used where heavy reasoning pays

Open-ended analysisReasons on a frontier model

Business layer

Stays under your control

  • Business rules
  • Persistent state
  • Data contracts
  • Integrations
  • Action semantics
  • Evaluation criteria
  • Operating history

The model is a component. The business layer is what persists.

Illustrative workloads and execution classes, not a live system · RAUNEM's own AI infrastructure places workloads on this principle

07 / Where to Start

Decide firstwhat not to build.

Bring a business problem. The first answer may be to buy something that already exists. Where a system is justified, it grows only as it proves itself.

A business problem

Decide the route

Buy

A mature product already does the job. We help you choose it and set it up. No custom system needs to be built.

Adapt

A product comes close. We make it work in your operation: your systems, your data, your rules, your approvals.

Build

The workflow is specific to your business. We build the smallest working core that can prove its value.

Evidence gate

  1. Your real cases, not demo prompts
  2. What “correct” means, agreed first
  3. Evaluated before autonomy expands
  4. You decide what expands

Operate

  • Monitor and evaluate
  • Adapt as models and APIs change
  • Maintain the integrations
  • Tune running cost, evolve safely

A way of routing a problem, not a fixed process

Bring the difficult part.

We’ll work out what the right next move is.

Describe the problem

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