Turn the data your business already has into results you can trust.
Speriential is the governed intelligence layer between your systems, your approved AI models, and the business decisions that follow. It verifies the evidence, applies exact rules and policy, and refuses when the available data does not support an answer.
No card. No call. No rip-and-replace.
- Evidence-linked
- EN · PT · ES
- Higher confidence in every answerEvery result cites the record it came from
- Built for real business useExact rules, policy and honest refusals, on your own data
- From proof to productionSee it in the Proof Workspace, then run it through the SDK
Watch it answer, then watch it refuse
Both panels below came out of the engine, not out of a copywriter. The figures were computed from records you can see cited, and the refusal is what it really returned when asked something its documents do not cover.
Answered
Refused
Why: No document on file mentions that topic.
Drive it on your own records
That run used our sample. Run the same governed intelligence on a controlled slice of your data the moment your application calls it through the SDK. Access is by invitation: ask above, and your access comes with the signed SDK and its install line.
Ask for access →That ran on our sample. Run it on a controlled slice of yours in the private Proof Workspace or through the SDK; ask for access at the top of this page.
Keep your systems of record. Add a system of intelligence.
Your CRM, support platform, billing system, warehouse, membership platform, and policy repositories remain authoritative. Speriential works across them to determine what the evidence establishes, what remains uncertain, and what the business is permitted to do next.
CRM. Accounts, contacts and their history stay in your CRM. Speriential reads the records it is granted and cites each one by its own id.
Evidence. Every answer names the records it rested on, so a reader can check it instead of taking it on trust.
Facts. A figure or a state with the records behind it, ready to be checked.
Models handle language. Speriential handles business truth.
Use models to interpret, extract, summarize, and communicate. Use Speriential to verify evidence, resolve identity and state, calculate exact values, apply policy, refuse unsupported conclusions, and control what happens next.
AI and semantic models
Built for interpretation and expression
A model reads 'can I still get my money back?' as a question about the refund window.
A model pulls the product, the date and the complaint out of a long email.
A model sees that 'nobody called me back' and 'still waiting on your call' are the same complaint.
A model writes the three-line summary a manager will read.
A model turns a table of figures into a paragraph in the reader's language.
Speriential
Built for business truth and control
Speriential decides which account this is and whether the case is still open, from the records on file.
Speriential checks that every cited record exists and actually carries the sentence that cites it.
Speriential computes the total from the rows in the period and states the rule that selected them.
Speriential applies the refund window in your policy to this member's own renewal date.
Speriential refuses when no document on file covers the question, and says what would fix that.
Speriential reads only the collections this seat was granted, and holds a dispatch for its approver.
Speriential lets an action proceed only when the policy's gate is met, and records who met it.
Speriential keeps the receipt: what was read, computed, removed and approved, for anyone to inspect later.
Models propose and communicate. Speriential determines what the business can trust and do.
Use an approved model. Keep one Speriential intelligence contract.
The outcomes teams put Speriential to work on.
The four we hear most often. Bring the one that is yours and watch it run on your own data.
Reduce costs or lost revenue
Where money leaks out of the work you already do.
Every reason people contact you, counted and grouped, with the records behind each figure. The work goes where the volume actually is instead of where it is assumed to be.
Boost productivity
Where the time actually goes.
Incoming work read and answered from your own material, with the ones that need a person marked as needing one. Your team opens those and not the rest.
Improve quality
What slipped, and the line that shows it.
Every answer cited back to the record it came from, and an honest refusal when your material does not cover the question. You can check any result rather than take it on trust.
Surface revenue opportunities
The openings already sitting in your data.
Accounts and moments worth a follow up, each pointing at the record that flagged it, so a next step is something you can act on the same day.
See it first. Then put it into production.
Use the private Proof Workspace to establish the value. Approved design partners can operationalize the same use case through a signed Speriential SDK distributed through the package workflow their company already trusts.
In the private Proof Workspace
A business question with its inputs and outputs named, so what counts as proof is agreed before anything runs.
Our sample collections, or a controlled slice of your own records brought in as a file or a paste.
The result, the records it cites, its groundedness, and what it declined to answer and why.
A gated link for colleagues, never public by default, carrying the same evidence they can check themselves.
Through the private SDK
The same question, data mapping and policy, called from your own application through the signed wheel.
Private SDK distribution for approved design partners
pip install ./speriential-0.1.0b2-py3-none-any.whlfrom speriential import Speriential
# your invitation's key, read from the environment
sp = Speriential()
result = sp.knowledge.answer(
"What is our cancellation policy?",
dataset_id=policies.dataset_id,
)Approved design partners install Speriential through a signed private package or their company's existing package registry. The SDK handles the integration contract; Speriential's hosted doors preserve the intelligence, governance, quality, and IP boundary.
Your reputation rides on every answer. So Speriential shows its evidence.
One confident wrong answer can cost a relationship, a claim, or your good name. So instead of asking you to trust a model, we show you the evidence: every result computed or retrieved from your own data, cited, kept private, and fully auditable. That's how you scale AI without ever betting the business on a guess.