01 · Agentic Data Flows

Your data isn't the problem.
The wait for it is.

The answer to your operator's question is already in your systems. It's just stuck behind seven logins, three SQL dialects, and someone's lunch break. We deploy a multi-agent system that reads, reasons, and answers — in plain English, in your environment, in 8–12 weeks.

Start a conversation See the agent stack

Minutes

From question to answered — not days

Legacy sources stitched into one workflow

100%

Citations — every answer traceable to source

Zero

Re-platforming. We read what's already there.

The problem

The answer exists. Just not in one place anyone can reach.

Your ops team isn't short on data. They're short on time to chase it across six systems built across three decades.

Siloed by accident, not design

Each system was the right choice the year it was bought. Together they form a maze your operators learned to navigate from muscle memory — and your new hires can't.

Reports lag the decision

By the time the Tuesday morning report lands, the issue it surfaces is already on Thursday's problem list. Speed of decision is bounded by speed of assembly.

Tribal knowledge isn't written down

The senior analyst knows that field X means something different in plant 2 than plant 4. When they retire or leave, that mapping leaves with them.

Replatforming isn't a real option

A two-year data lake migration to fix a six-week question is the wrong answer to the wrong question. The data already exists — you just can't get to it fast enough.

The approach

Specialist agents. One coordinated answer. Plain English in, traceable answer out.

One big monolithic model can't read your ERP, reason about your business rules, and cite the result. We split the work: small, swappable agents — each doing one job well, orchestrated to answer the question end to end.

Agent role

What it actually does

Router agent

Reads the question, picks the right specialists, sequences the work

Source connector agent

ERP, MES, CRM, ticketing — speaks whatever protocol they expose

Schema agent

Maps fields between legacy systems where no one wrote the schema down

Reasoning agent

Combines facts from sources, applies your business rules, drafts the answer

Citation agent

Every claim is traceable back to row, file, ticket, document

Escalation agent

If confidence is low, routes to the human who actually knows

Audit agent

Logs the question, the path, the answer — for compliance and review

All seven agents run as a coordinated team. Every answer is cited. Every escalation is logged. Each agent is a small, swappable model — add a new source or specialist by adding a row.

How we're different

We're integrators. Not a platform you have to license forever.

The agentic AI market is full of vendors who'll sell you their platform, their cloud, their seat fees, and a multi-year contract. We don't. We assemble the right agent stack for your problem from the best building blocks — and we leave it running clean.

No vendor lock-in

Open weights where possible, your data stays in your environment, your business rules in your repo. When the engagement ends you keep what was built — including the right to swap us out and have someone else run it.

Best model for the agent

Different agents need different brains. Routing wants a small fast model. Reasoning wants a frontier model. Citation wants a deterministic retriever. We pick per agent, not per platform.

Leverage what you already own

If your ERP, MES, ticketing, or data warehouse already holds the answer — we connect to it. No re-platforming, no "first you migrate everything to our lake," no rip-and-replace.

Integrator, not platform vendor

We don't sell an agentic platform you have to license forever. We assemble the system from open building blocks — open-source orchestration, your data systems, your auth — and we walk away when it's running clean.

How we deliver

Walk-through to working command center in 8–12 weeks.

01Wk 1–2

Scope

Walk the workflow. Inventory the systems already in play. Pick the question or report that costs the most to answer today. Define the success number — turnaround time, accuracy, coverage. Written. Signed.

02Wk 2–4

Connect

Stand up read-only connectors to your existing systems. No replatforming. The agents query what's already there.

03Wk 4–6

Model

Assemble the agent stack against your data. Each agent has one job and is swappable. Your business rules, your taxonomy, your guardrails.

04Wk 6–10

Deploy

Shadow mode against your real workflow. We tune routing, citations, and escalation thresholds before the system answers a single user question on its own.

05Wk 10–12

Cut over

Flip from shadow to live on your timeline. We stay hands-on through the first weeks of real questions and real users.

0612 mo

Operate

We stay on. New source system? Add a connector. New question pattern? Add a specialist. Hours, not quarters.

What changes

Decisions land in minutes. Answers come with their receipts.

Every engagement has a success number signed before week one. Milestone-gated payment. You pay for results, not for hours.

Every answer is cited

Source row, file, document, ticket. Auditors and skeptics get to verify, not just trust.

Low-confidence routes to a human

The system knows when it doesn't know. Escalation goes to the person who actually has the answer — not a queue.

Add sources without redesigning the system

New ERP module, new CRM, new spreadsheet? Add a connector. The rest of the agents don't care.

Stack at a glance

Sources

ERP, MES, CRM, ticketing, data warehouse, spreadsheets, PDFs

Orchestration

Open-source agent framework. Your code, your repo.

Models

Per-agent: small/fast for routing, frontier for reasoning, deterministic for retrieval

Auth

Your IdP. Your roles. Your row-level permissions, respected end to end.

Audit

Every question, every path, every answer — logged for review

Hosting

Runs in your environment. Air-gapped if needed.

Lock-in

None. Open weights where possible, your data, your right to swap us out.

Common questions

What ops leaders ask first.

We don't have a data lake. Is that a blocker?

No. We don't require one. The agents read what's already in your source systems — ERP, MES, ticketing, spreadsheets — through their existing interfaces. If a data lake is on your roadmap, fine; if not, also fine.

What stops an agent from hallucinating a number?

Two things. First, the citation agent — every claim is bound to a source row or document; if it can't be cited, it doesn't ship. Second, the escalation agent — when confidence is below threshold, the question routes to a human instead of a guess.

How do we control what each agent can see?

Your IdP and row-level permissions, respected end to end. The agents query as the user who asked the question. If they can't see it in your existing systems, the agent can't see it either.

Who owns the agents and the data?

You do. Both. The system runs in your environment, your orchestration code lives in your repo. We don't resell your data, train shared models on it, or hold orchestration hostage behind a license.

How is this priced?

Outcome-based, milestone-gated. We agree on a success number — turnaround time, accuracy, coverage — before week one. You pay when we hit it. Twelve months of operating support is included.

Start with one question

Pick the report that takes the longest to assemble. We'll show you what Day Two looks like.

One conversation, one workflow, one signed success number. That's the on-ramp.

Start a conversation Read the field notes

Your data isn't the problem.The wait for it is.