AI that understands
your business.

We help businesses build their own AI systems + infra.

The companies that win aren't the ones waiting for AI to mature. They're the ones building with it now.

§ 02

Today's reality:Fragmented tools. Scattered data.

§ 03

What we build.

§ 01

Data foundations and governance

+
↳ Includes
01Multi-source ingestion

Pull from APIs, documents, public sources, legacy systems. Raw payload preservation. Schema evolution without re-running migrations.

02Classification and governance

Tooling that lets non-technical operators classify their own data. Source-of-truth maps, nomenclature dictionaries, risk scoring. Outputs a layer AI agents can read.

03Audit and compliance

Append-only ledgers. Route-layer policy enforcement. Every decision reconstructable. Regulated industries pass on review.

04Postgres-native lake

Operational and analytical data in one Postgres store. Sub-second joins, single source of truth. Sunset the warehouse and the ETL pipeline.

§ 02

Production AI infrastructure

+
↳ Includes
01Structured output

Typed schemas all the way through. No regex parsing of freeform text. Anti-hallucination at the boundary, not as a prompt instruction.

02Observability and telemetry

Per-generator stats on calls, latency, cost, tokens, cache hits, retries, fallbacks. A health endpoint that catches drift before customers do.

03Route-layer compliance

Policy enforced at the API boundary, not as a code-review item. Regulated industries pass review the first time.

04Append-only audit

Every AI action and every analyst override logged immutably. Every decision reconstructable, no soft deletes, no overwrites.

§ 03

Working brains

+
↳ Includes
01Source synthesis

Pulls from public web, internal data, and the specialty feeds your team already trusts. Dedup, classification, brand disambiguation, source-linked audit trail.

02Briefs that reason

Not a list of headlines. Cross-item synthesis that names what changed, why it matters, and what to do next.

03Memory and pattern detection

Rolling archive the brain reads from. Trends called out before they're obvious. Connections across stories a human would miss.

04Conversational interrogation

Ask the brain in plain language. What changed since last Friday. What questions to be ready for at the next board call.

§ 04

Operating systems

+
↳ Includes
01Multi-source data layer

Pulls from APIs, document stores, public sources, legacy systems. Raw payloads preserved. Cross-source entity resolution into one canonical view.

02Decisioning and scoring

Multi-dimensional scoring with versioned weights and human override. Every decision reconstructable from the audit log.

03Daily working tools

Dashboards, pipeline views, comms drafting, document generation. The platform the team opens first thing in the morning.

04Executive intelligence

Board deck generators, exec briefs, real-time queries in plain English. Built for the seat reading them.

§ 04

Field notes.

All entries
§ 05.01 · Featured7 MIN
PLATE · 05.01
MAY · 15 · 2026
Primer

How AI agents actually work: a non-technical primer.

'AI agent' is one of the most-used phrases in AI right now, and one of the most loosely defined. Here is the clearest one-sentence version, and how agents actually work underneath it.

CSCharlie StonerCo-founder
AgentsTool-usePrimer
Read entry
Primer·By James Finnegan

RAG, retrieval-augmented generation, is the most useful AI architecture for a business that has its own data and wants AI to actually use it. Here is what it is, how it works, and the three questions that decide whether your business needs one.

RAGWorking brainsArchitecture
Read entry
Concept·By James Finnegan

An AI business operating system is the connected layer a company's operations run on. Not a tool you add. The system underneath. Here is what one is, why a business reaches the point of needing one, and how a real one is built.

Operating systemsWorking brainsStrategy
Read entry
Concept·By James Finnegan

An AI tool is a single function: a chatbot, a summarize button, a search box. An AI system is the architecture that connects functions together so they read your data, reason about it, and produce something an operator acts on.

Tools vs systemsStrategyPilots
Read entry
§ 05

Cards on the table.

01
016WSPAN
2–16wks
Time to production
From a single integration to a full operating system. Weeks, not quarters. Because the stack and the team are built for it.
02
TRADSTR
1team
From scope to ship
Strategy, build, deploy. The same people from first call through launch. No handoffs, no junior bench, no agency layer cake.
03
OWNEDOURS · 0
100%
Yours to keep
Your repo, your accounts, your data. We build it, you own it, and we keep shipping alongside your team as the system grows.
Selected cases
§ 06

How we work with you.

Discovery
1–3 weeks

We listen, map your operation, and find the first piece where we can show immediate impact.

Pilot
1–4 weeks

We build that first piece. Production-grade, on your real data, in your stack.

You own it
Forever

Your repo. Your accounts. Your data. No license, no lock-in.

Keep building
Ongoing

If the pilot lands, we stay on retainer. Same standard, same team.

§ 07

You bring the problem.
We ship the system.

Or writeinquire@straterai.com
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