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Engineering notes on what it actually takes to ship AI systems inside regulated enterprise workflows: retrieval, agents, evals, and the human review layer that holds it all together.

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Polemos Labs — AI Systems for Enterprise Operations

Polemos Labs is an applied AI studio. We turn fragmented data, manual review, and tool sprawl into governed AI systems that sense what matters and route the next move — keeping humans in command.

The problem: command is hard

AI fails when it is bolted onto broken process. The hard work is the wiring.

Workflow terrain mapped before model choice
Private data connected with permissions intact
Human command where risk is high
Production telemetry from day one

What ships

Finance & Operations — invoices move from inbox chaos to controlled exception queues

Ingest PDFs, emails, and ERP records; validate fields against policy; escalate only the decisions that need a human owner. Replace manual chasing with governed review loops.

Logistics & Supply Chain — demand signals become procurement moves before pressure hits

Connect transaction history, supplier data, and live operational context so planners can act before bottlenecks become expensive. Turn forecasts into triggers, not another dashboard.

Professional Services — institutional knowledge becomes a cited analyst layer

Build retrieval, citation, and synthesis systems across contracts, research, tickets, and client records. Senior teams spend less time searching and more time deciding.

Implementation accelerators

OmniGraph — Grounded Retrieval Layer

Production retrieval stack. Answers grounded in your data, with citations.

Hybrid search and rerank for high-precision recall
Permission-aware grounding across your systems
Eval harness for precision, recall, and faithfulness

NeuroTask — Supervised Agent Runtime

Graph-based agent runtime with typed tools and human approval gates.

Supervisor and worker agents on a typed state graph
Schema-validated tools, sandboxed and least privilege
Human approvals on destructive actions, with full traces

Core services — built to ship

AI Opportunity Mapping

We identify the workflows worth automating, the data required, and the fastest route to measurable production value.

Ingestion, Retrieval & Knowledge Graphs

Pipelines, indexing, permissions, and RAG systems that make internal data usable by people, agents, and decision systems.

Agentic Workflow Automation

Agents that execute bounded tasks, use tools, validate outputs, and hand off to humans at the right moment.

Model Deployment & Tuning

Open-source model deployment, evaluation, fine-tuning, and monitoring for teams that need security, cost control, and auditability.

How we work — validate before scale

01 / MAP — Discover (2 weeks): Map high-friction workflows, data readiness, risk, and ROI. You leave with a prioritized implementation brief.
02 / DESIGN — Plan (3 weeks): Define architecture, model strategy, integrations, evaluation sets, and human-in-the-loop controls before code.
03 / DEPLOY — Execute (4–6 weeks): Ship the first production workflow with ingestion, retrieval, agents, tests, observability, and real user feedback.
04 / EXPAND — Command (ongoing): Harden the system, expand to adjacent workflows, monitor quality and cost, and train your team to operate it.

Who we work with — real stakes only

You have a specific operational bottleneck with measurable cost, delay, or risk
You own proprietary data that should become a strategic advantage
You need secure deployment across existing tools, teams, and approval paths
You measure success by business outcomes, not model benchmarks or prototypes
You have the mandate to ship and a team ready to own the system after launch

Contact

Email hello@polemos.in or visit polemos.in.

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