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GroundSetTM
Walkthrough
Platform01Proof02Trust03Company04
GroundSetThe platform

One engine. Four layers. One record.

Models read messy reality. Your rules decide. Every outcome routes with its justification and is set in a ledger that lives inside your perimeter. The four verbs from the homepage — Understand, Decide, Route, Set — run on the four layers below.
01Architecture

Perception → Context → Judgement → Execution.

  1. Perception01

    Reads the evidence.

    Domain-trained SLMs and VLMs read documents, images, voice and video — handwritten ledgers to camera feeds.

    in   scans · IDs · voice · video
out  facts + confidence
  2. Context02

    Grounds the facts.

    Joins what was read to the case it belongs to: the account, the policy terms, the site, the prior decisions.

    in   facts
out  grounded case
  3. Judgement03
    Policy Engine

    Applies your rules.

    The Policy Engine. Your policies, thresholds and SOPs, encoded as versioned rules and evaluated deterministically.

    in   grounded case
out  outcome + justification
  4. Execution04

    Acts, with reasons.

    Approves, rejects, holds or escalates to a named human role, and writes back to your core systems and queues.

    in   outcome
out  route + action
Decision ledgerevery layer writes here · immutable · replayable

The Policy Engine is the moat.

Models read; rules decide. Your policies are encoded, versioned and owned by you, and every decision is recorded against the exact version that made it.

Change a threshold and the ledger shows every decision on either side of the change. That is what makes judgement reviewable — by your risk committee, your auditors and your regulator.

02The ledger

Anatomy of one decision. This is the product.

Specimen record · values illustrative
record_id
dl_2026_09_28_000417
case
MSME-LN-88213
evidence[0]
handwritten_ledger_0447.jpg · sha256:9c1e…a04b
evidence[1]
id_scan.png · sha256:41f7…0c2d
facts
monthly_revenue ₱412,300 (0.987) · debtors 14 (0.962)
rule
MSME-CREDIT-114.v12 · dscr ≥ 1.25 · PASS
outcome
APPROVE · limit ₱180,000
route
auto
confidence
0.981
override
none
latency
47ms
prev_hash
0x77d0…19be
hash
0x8f3a…c41d
01Evidence
Every input, fingerprinted. The document itself is purged after processing; its hash stays, so the record proves what was seen without keeping it.
02Rule version
The exact rule and version that decided. Rules are versioned like code — nothing decides against an unrecorded rule.
03Outcome
The decision and its route, with the justification that travels to whoever acts next.
04Confidence
Per-fact extraction confidence. Below your threshold, the case routes to a person instead of guessing.
05Override
When a person changes the outcome, who, when and why is set in the same record. Judgement stays attributable.
06Hash
Each record is chained to the one before it. Alter one and the chain breaks. Any decision replays end-to-end.
03Deployment

Inside your perimeter. In three weeks.

GroundSet deploys in-VPC or fully air-gapped. The first production workflow is live three weeks from kickoff. Here is what your InfoSec team will review, and what they will find.

Mode · In-VPC

Models, Policy Engine and ledger run in your cloud tenancy. Inference makes no external calls.

Mode · Air-gapped

On your hardware, with no network path out. Updates enter through your own change process.

What your InfoSec team reviews

01Network
No egress at inference. The only inbound path is the one you open.
02Data handling
In-memory processing, purge on completion, zero retention.
03Access
Who can read the ledger, change rules and override decisions — enforced inside your environment.
04Model provenance
Open-weight base models, post-trained in-house. Composition disclosed under NDA.
05Testing
VAPT results and the security annex, shared under NDA.
Open the Trust Center
04Model doctrine
Open-weight base models, post-trained in-house, running entirely inside your perimeter. Composition disclosed under NDA.
05Objections, answered

Plain answers to fair questions.

01Isn’t this an LLM with a prompt?
No. Models read; they do not decide. Extraction produces facts with confidence scores, and your rules — not a model — produce the outcome. Same input, same output, every time. There is no temperature in the decision path.
02Why not a copilot?
A copilot suggests and a person decides, so the record is still whatever that person remembers. GroundSet decides within rules you set, routes exceptions to people with the reasoning attached, and records both. Accountability lives in the ledger, not in an inbox.
03Why does the record compound?
Every decision is set against a rule version with its evidence. Over time the ledger becomes the institution’s memory of judgement: which rules held, where people overrode, what changed when a threshold moved. It grows with every decision, and it is yours.
04What happens when the evidence is unclear?
Confidence below your threshold routes the case to a person, with the evidence and the partial reading attached. The engine never guesses its way into an approval.
06Next step

See one real workflow become infrastructure.

We map one decision workflow from your operation and show it running end-to-end — understood, decided, routed, and set in the ledger. Thirty minutes, your data patterns, no slideware.

Or the decision infrastructure required.