The agentic AI platform for supply chain operations
Put an agentic workforce to work across your supply chain and operations
Authentica's AI agents do the operational work, from procurement to payment: auditing invoices, verifying compliance, optimizing and reconciling orders, recovering overpayments. They reason over a living model of your business, execute the work, and escalate the judgment calls. Grounded in your data. Governed by your rules. Live in weeks.
The operating surface
Hire a workforce. Run the operation.
Give each agent a role and connect it to your systems, then run the whole team from one surface: delegate the work, set what needs your sign-off, and see every action the moment it happens.
01Value pillars
Recover overpayments. Catch oversights. Cut the cycle time.
Every workflow we automate targets one or more of these measurable outcomes, starting with the money you are owed right now.
01 Reduce.
Cut the manual hours and the cost per transaction, often dramatically, on the highest-volume work in your operation.
02 Mitigate.
Catch the errors and compliance gaps before they cost you. Every action logged, so every dispute is short.
03 Capture.
Recover the money already owed to you, from freight overcharges to duty refunds, with the receipts to prove it.
02Customers
Real operations. Real teams.
"Authentica is what the next decade of supply chain looks like, and we've got a head start. Their agents have helped us recover thousands in tariff overpayments and stay on top of our shipments and freight charges. They plugged into our systems, mapped how we run, and stood up agents that work like members of our team. Now we're expanding into demand and supply planning, so we can run leaner inventory and respond faster to our customers."
"As we scale globally, freight spend and tariffs are a growing cost and risk. Authentica doesn't just flag the errors, it does the work: it codes our freight invoices, drafts the disputes, and builds the evidence to recover what we're owed. In the first couple of months it surfaced tens of thousands of dollars in recoverable charges we'd likely have missed, and gave us cost visibility by line of business that we didn't have before."
03How it works
See how it works
Real workflows, real results. Here is what our customers automate across the supply chain lifecycle: Plan, Source, Move, Receive, Comply, Pay.
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Plan
02
Source
03
Move
04
Receive
05
Comply
06
Pay
04How we work with you
See it work before you commit
01
See the speed first.
We build a custom workflow demo on sample data so you can watch an agent do the actual work in minutes. No data of yours required to start, and nothing touches your systems until you decide to move forward.
02
Your data and your build stay yours.
When you move to deployment, everything runs in a single-tenant environment, encrypted, never trained on, never used for anyone else. The workflows and any software we build are proprietary to your business, owned by you, and portable if you leave.
03
Scale what works.
Once you see the results on your own operation, expand to the next workflow. The console to stand up the next one is one click away.
An AI forward-deployed engineer builds your deployment.
The line workers are agents: they read your operation, draft your operating model, write your benchmarks, and open the pull requests. People review everything that ships.
Stage 01 · Discovery
Read the operation
Agents ingest your SOPs, transcripts, spreadsheets, and data dumps, and produce a grounded map of how your operation actually works.
agents do the workStage 02 · Ontology
Draft the operating model
The operation is encoded as a typed spec: entities, events, actions, tasks, validated against structural rules before anyone reviews it.
agents draft · humans reviewStage 03 · Evals
Write the benchmark
Real scenarios from your workflows become hand-labeled gold cases: the benchmark your agents must pass before they touch production.
agents generate · humans labelStage 04 · Ship
Open the PR
Every artifact lands as a pull request. One gated write-path, full audit trail. The agents write; people sign.
humans approveBuild
The line stands up your deployment. Every artifact is a draft for review. You're not live yet.
Evals
You run the system against your real workflows. Every miss becomes a gold case, so the eval suite only gets harder before go-live.
Live
Agents make real decisions in production, with drift watch and human supervisors at every escalation point.
Exit criteria, not calendar dates. Each phase ends when the benchmarks pass and you sign off, not when a quarter does.
05The platform underneath
Everyone sells visibility. We build the layer underneath.
Dashboards tell you what happened. They don't decide what to do next, and they don't do it. Authentica builds a living operating model of your business, not your warehouse, not your ERP, your business, and puts agents to work inside it. The AI reasons; your business rules execute. Nothing mission-critical depends on a model's creativity, and nothing depends on one model vendor.
06The engine underneath your supply chain
Demo-grade AI impresses. Decision-grade AI answers for itself.
Most enterprise AI is demo-grade: brilliant in the meeting, unaccountable in production. Decision-grade AI passes four tests.
Test 01
Grounded.
It acts on your real records and your operating model, not free text. If a fact isn't in an authorized source, the agent can't invent it.
Test 02
Validated.
Every change is tested against your own history in a grading harness before it ships. Only score-improving changes survive.
Test 03
Gated.
A human approves anything that matters. 95% handled autonomously, the uncertain rest escalated, every action logged.
Test 04
Auditable.
Every action carries its reasoning and its receipt. Show anyone exactly what happened, when, and why.
Approximately right is expensively wrong.
07Why now
The cost of intelligence collapsed. The cost of standing still didn't.
Agentic AI in supply chain just crossed from experiment to table stakes. Operators are running agents in production today, auditing every invoice, recovering duties, compressing cycle times. The gap between the teams that moved and the teams that waited widens every quarter.
08Enterprise-grade
Your data is safe. Your build is yours.
For regulated industries, AI governance is a requirement, and data sovereignty is the first question procurement and legal ask. We built Authentica so the answer is settled before the conversation starts.
Your data stays yours.
Single-tenant by design. We never train on your data, and we never use it for your competition. Encrypted at rest and in transit. You keep full ownership and control.
Your workflows and builds are proprietary to you.
The operating model, the workflows, and any software we build are yours: owned by you, never shared or reused across customers, and portable if you ever leave. Not broker-owned. Not pooled.
AI you can audit.
Every agent decision is traceable. Full reasoning logs, human-in-the-loop controls, and deterministic execution where it matters.
Runs on the mess you already have.
No rip-and-replace. Agents slot into the tools your team already uses. Backed by SOC 2, SSO/SAML, and encryption at rest and in transit.
The questions worth asking any AI vendor
What are your agents doing with our data, and who owns what gets built?
Everything you build on Authentica is yours: the workflows, the integrations, and any software we build for you, all your IP. The only thing that is ours is the operating model and the enforcement layer underneath. We are SOC 2 Type II, independently audited by Prescient Assurance, with the report available under NDA. We run on AWS, and nothing you put in trains any external model. Whatever you build stays on your own farm, and it is in writing in the MSA. When you looked at other tools, did anyone walk you through where your data lives and who owns what gets built? That is usually where the answers get fuzzy.
What happens to our people if the agents do the work?
The job rarely disappears. It changes shape. The person who spent eight hours on status emails becomes the one who handles the 5% of exceptions that actually need judgment, plus the higher-value work there was never time for. The model is built for it: 95% handled autonomously, the uncertain rest escalated to your team, every action logged. Your people stay in the loop and in control. We start with one workflow and one team and let the redesign follow the results, not a big-bang reorg.
If AI runs the workflows, what is our value?
Your value was never the 25 emails it took to book a shipment. It was the judgment, the relationships, and the service promise. The admin work just buried it. When the agents take the status work, what is left is the part your customers were paying for. In one case, an inbound QA cycle that used to run for months now takes weeks, freeing capacity for materially more volume without new hiring. The team did not shrink. The throughput grew.
We tried an AI chat tool and nobody used it. Is this just another chat window?
No, and it is why we do not lead with one. The agents run inside the systems your team already works in: the WMS, the TMS, the AP inbox. Work shows up as approvals, alerts when a human is needed, and screens built for the task. Prompting is one way in, not the product. If your TMS only does 90% of what you need, we build the missing 10% as real screens your team uses, and those screens are yours to keep.
Is the first workflow just a foot in the door to our data?
No. Because you own everything built on your data, the only reason we grow inside your business is that the first workflow paid for itself and you asked for the next one. We scope tight on purpose: one workflow, one measurable result, then you decide. If we do not earn workflow two, we do not get it.
See a custom workflow demo within a week.
We build a workflow demo on sample data so you can see the speed and exactly how an agent handles your kind of work. Nothing to hand over to see it run. Your data, your workflows, and anything we build stay yours and protected from day one.
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Book a demo 1-2 days02
Workflow demo 3 days03
Onboarding 1 week04
Scale-up 3 monthsStart here
Where to go next
White paper
The Model Is Not the Product
Why reliable AI runs on an operating model, not a bigger model. The result we measured, and how.
Read the paperCustomer proof
Real operations. Real teams.
In production across food, defense, retail, industrials, and manufacturing.
See the customersJust shipped
Studio
Where your deployment gets built and authored, by agents and your experts together.
See the build surfaceEngineering
Harness Engineering
How we make AI reliable for supply chain operations, not just fast in a demo.
Read the article