Chaos in.Order out.
Where AI actually pays in your operation; found in weeks, proven with numbers your CFO will accept.
Three ways in: advisory for engineering organizations, fixed-scope AI agent builds, and productized systems you can buy directly.
Ordinara exists to close the gap between what AI promises and what a business actually banks, measured in hours returned, cost removed, and software shipped.
Every tool owns two links and drops the rest.
The gap between one link and the next is covered by your people, by hand.
A requirement leaves in an RFQ and has to survive all the way to the test that validates it and the change order that re-prices it. No category of software follows it the whole way: CRMs stop at the sale, PSA tools bill the project but do not know what a requirement is, ALM suites own traceability and have never seen a lead. The trip happens by hand, across four tools and a spreadsheet.
- Marketing contact to qualified leadNobody can say which campaign paid for the deal, so budget is set by argument instead of by cost per acquisition.This one we solved on our own site: a message that arrives here carries the campaign it came from.
- Lead to saleThe CRM holds the relationship and has nowhere to put the engineering content the deal actually turns on. That content lives in email and folders, and whoever inherits the account rebuilds by hand what was already agreed.
- Sale to RFQ with requirementsTier 1 and Tier 2 suppliers take two to three weeks to answer an OEM RFQ. Margin is decided in those weeks, by hand, under time pressure.
- Requirement to contractWhat the quote promised is retyped into the contract. What gets dropped in the retyping is discovered at delivery.
- Contract to delivery with traceabilityYou can show the customer the work, but not which requirement each test was validating. That is the question the audit asks.
- Engineering change to P<he change is agreed in engineering and re-prices the program. Finance finds out at the close, when nothing can be renegotiated.
Covering those six links by buying licences runs $60,000 to $120,000 USD in the first year, every year after that, and at the end of it you own none of it. I build the one system where the trip does not break, on top of the tools you already pay for, paid once, and it is yours.
That spend is on licences, not on Ordinara. Modelled on 25 users: project management seats $8,000 to $20,000 a year, CRM and marketing $10,000 to $25,000, engineering tooling with traceability quoted per seat, and integrating them to each other $20,000 to $50,000 in the first year.
Sources: RFQ response times and the cost of assembling equivalent coverage from CRM, PSA and ALM licences, from Ordinara's own market analysis, August 2026.
Fixed scope. Fixed fee. Engineering deliverables.
Your teams adopted AI everywhere; nobody can prove which half is real → an evidence-based map of where AI pays, and where it quietly writes liabilities.
AI leverage audit
Fixed-fee, read-only diagnostic: where AI genuinely cuts cost, with measured evidence, and the findings your own tools can't surface about themselves: tests that assert nothing, phantom traceability, gamed coverage.
Your AI reviewed your architecture and found nothing → a half day showing, on your artifacts, what it can't see about itself.
Executive AI evidence session
Bring one architecture and your AI's review of it. Live: where an independent read disagrees, and why. You leave with three written decisions. Prepaid, 100% creditable against any engagement.
Your OEM's assessment has a date → the audit before your audit: zero surprises left for the day that counts.
SDV audit-readiness sprint
Assess: gap grid + evidence inventory against a published SDV reference. Rehearse: a game day with your team on a zero-egress instrument your security can inspect line by line. Coach: the evidence trail fixed together. Referees certify; this is the coach.
Teams shrink, AI accelerates, evidence debt compounds → the outside answer key on retainer. Exits monthly.
Fractional AI advisor
Monthly evidence reviews, a rehearsal before every customer gate, AI-governance guardrails, and a memo written to be forwarded upward. Four hours a week alongside a VP; either side exits monthly.
Your workflows on the table; the delivery system shown running. Read-only access, scoped and revocable.
Structured interviews plus read-only repo and pipeline probes; hours quantified per area.
Every opportunity scored on impact, feasibility, risk and adoption friction.
20–30 pages with the ROI math shown, plus a 60–90 min executive readout.
The deliverable: the leverage map with the math shown, the slop findings, and a 90-day pilot roadmap.
AI agent builds for US SMBs
A workflow everyone agrees should be automated, still done by hand → a working agent on your accounts, with a signed acceptance test.
One AI workflow, built and shipped.
For founders and small teams outside automotive and embedded, a single fixed-scope agent build, from the same delivery system, no safety-critical framing required.
- A working agent running on your own accounts
- A signed acceptance test, agreed before the build starts
- The source code in your repository, owned by you
- Documentation and a handoff walkthrough
Private AI solutions
Productized, single-tenant private AI, proven in production. The system runs on your own accounts, so nothing is handed to a third party.
- Single-tenant by design, never a shared instance
- Your accounts, your data, your keys, with no access retained
- Proven in daily production use, not a prototype
One delivery system. Three tiers, simple to complex.
Private AI solutions
Productized, single-tenant private AI. Proven in production.
Example: Family Finance Dashboard
from US$3,500Buy directly →Book a call →Try the live demo →AI agent builds for SMBs
A defined agent, built and delivered. Fixed scope, fixed fee.
Examples: linkedin-agent · CV Maestro
from US$9,500Buy directly →Book a call →Engineering-organization advisory
Diagnostics, evidence sessions, fractional advisory and SDV audit-readiness sprints, for organizations that ship software into vehicles.
Fixed fees US$6,500–18,000 · entry session from US$1,500Book a call →Booked on a call, then invoiced by Ordinara LLC. 50% at signature, 50% on delivery. Working sessions are prepaid.
You are not paying for people. You are paying for judgment: no juniors, no overhead, no 200-slide deck. The scope is small on purpose and the rate is senior.
Built, shipped, running.
The worked example: linkedin-agent, Ordinara's own content engine
It researches each topic, drafts the post and prepares a companion document; a person approves every publication before it goes out. Three numbers, measured end to end, tell the whole story:
That pattern is the point: once a workflow is engineered as a system, the cost of running it collapses. In the first half of July 2026, Ordinara's entire production stack, the content engine above, the document pipeline and the finance assistant, ran on roughly US$6 of AI inference, measured by live per-call cost accounting. The build is what you pay for once; after that the operation costs cents, and senior time moves from producing to approving.
The founder's own household system, in daily use.
Ordinara's own commercial operation, running the business daily.
A fixed-scope agent build, delivered end to end.
A fixed-scope build for one defined workflow.
The four-domain reference behind the audit-readiness sprint.
Every system here can be demonstrated live, in the first meeting, on request.
Built with Claude (Anthropic), OpenAI and Gemini as the problem requires; agent architectures with MCP and RAG.
Order,deliveredasasystem.
One production AI delivery system. Three tiers of engagement. Zero custody of your data.
Proven on safety-critical programs.
Digital clusters losing illumination in the field, root-caused and fixed in firmware across five sites, no recall and zero hardware change.
A dual-processor cluster program in technical debt, driven to feature-complete on a fixed launch date across three continents.
A first-of-its-kind aftermarket telematics line, defined and launched from zero by a five-engineer team.
Occupant-detection ECUs going brain-dead during reflash, fixed at the memory-boundary level for a zero-defect Start of Production.
The systems, drawn the way they were built.
More than two decades leading organizations that delivered under Functional Safety, Cybersecurity and ASPICE discipline.
Automotive software at OEM and Tier-1 scale: safety-critical delivery, distributed teams, production releases. Now applied to one question, where does AI genuinely cut cost and cycle time in an engineering organization.
What drives the work is a single conviction: organizations of every kind keep paying, again and again, for the same avoidable pains, and most of those pains yield to engineering rather than improvisation. Ordinara exists to bring that engineered rigor to the problem, so the fix holds and does not come back.
Education: MBA, Tecnológico de Monterrey (ITESM); BEng in Electronic Engineering, Instituto Tecnológico de Querétaro.
Agustín Carrillo · FounderRead the deliverable before you buy it.
Every engagement on this page produces a written artifact. Four of them are published in full, on fictional clients, so you can judge the work instead of the pitch.
AI leverage audit
A sample readout: findings, the evidence behind each one, and the ledger that scores them.
Read the sample →Executive AI evidence session
What a half day produces: where an independent read disagreed with the AI, and the decisions that followed.
Read the sample →SDV audit-readiness sprint
The gap grid and evidence inventory a supplier takes into the assessment that counts.
Read the sample →Fractional AI advisor
The monthly memo, written to be forwarded upward without editing.
Read the sample →
Every system here can be demonstrated live, in the first meeting, on request.
Tell me the process that eats most of your week and in 48 hours you see it running, with sample data from your field. At no cost.
Your code, your accounts, your repo: the build ships into your GitHub and your cloud accounts, in your name.
No custody: your accounts, your data, your keys, we retain no access.
Single-tenant by design.
The most effective protection is the data we never hold.
The delivery system is disclosed, never disguised as staff, verifiability is the moat.
Security posture in writing, available to your procurement team on request.
Agustin is an extremely capable engineering group manager. He knows well how to get the most of his team […] I would work with him again for sure.
He is certainly a well rounded and experienced embedded software engineer and manager.
He was also the Person of Contact for a high visibility project for one major automotive OEM during the whole transition phase. He is technically savvy, pays attention to detail, and always delivers.
Four steps. No surprises.
Diagnostic call
30 minutes, no cost. The problem, the fit, and whether we should work together at all.
Closed proposal
Scope, fixed fee, timeline and acceptance criteria, in writing.
Deposit to schedule
50% books the start date. ACH, wire or card, invoiced by Ordinara LLC in USD.
Delivery against acceptance
Built to the signed criteria. Balance on acceptance, not before.
Corporate terms: deposit plus net 30. Payment details travel on the proposal and invoice, never by email request.
FindwhereAIpaysinyourengineeringorganizationoryourbusiness.
A 30-minute call. Fixed fees, engineering-grade deliverables, and claims that survive due diligence.
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