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semantic control layer · enterprise ai

The control layer that lets you wield AI with confidence

Govern the input, context and output of your AI pipeline. Every score calibrated, every veto deterministic, every decision traceable to the passage that triggered it.

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filingsreportsemailscallscontracts

Your Semantic Control Layer

calibrated signallayer 02

supply_chain_disruption {   score 0.86   valence negative   confidence 0.95 }

→ passage 14 · q3_filing.pdf

vetopass · deterministic

businessIndustry semantics for your sector: supply chain, counterparty and market risk.

01 the problem

LLM outputs are probabilistic. Regulated decisions can't be.

In regulated enterprise use, a non-conforming or inaccurate output that reaches a customer, a regulator or a downstream system is unacceptable. Validating at scale needs precision, auditability and configurability. The usual tools fall short.

Enforce Policies Before Agents Actdeterministic

01  llm output

The amended Q3 schedule is filed under Annex B, as required by the revised terms.

probabilistic

02  concept scores

regulatory_conformance0.94
source_grounding0.91
disclosure_complete0.88

03  route

verdictpass
downstream≥ 0.85
human review< 0.85
same input, same verdict, every run

02 the difference

Similarity finds what looks alike. Relevance finds what matters.

similarity searchthe model alone

Returns what looks alike.

  • 01High false positives
  • 02No context understanding
  • 03Same passage, a different answer every run
forgeai relevancecalibrated

Identifies what matters.

  • 01Semantic control layer between text and model
  • 02Calibrated confidence on every match
  • 03Full traceability at scale

03 who it's for

Structured inputs.Controlled context.Defensible outputs.Measurable outcomes.

your ctostructured inputs

Can't make sense of scattered, unstructured information

The answers are already in your systems, but trapped in PDFs, emails, and siloed data lakes.

Engineering ends up rebuilding the same extraction logic for every new document type, every new source, every new schema.

unstructured datasiloed sourcesbespoke pipelines
your coocontrolled context

Can't trust agents that operate without controlled context

Every decision depends on which policies apply, which data is relevant, which exceptions matter. Get any of it wrong and the agent acts on the wrong information.

Hard-coding context into pipelines doesn't scale. Letting the model guess is worse.

agent reliabilitypolicy enforcementdecision context
your crodefensible outputs

Can't defend decisions without an audit trail

Critical decisions carry real consequences for customers, regulators, and the business.

Every output is grounded in a source, a concept, and the evidence chain that links them.

source provenanceconcept traceabilityregulatory defensibility
your cfomeasurable outcomes

Can't greenlight another AI project without proven value

Every AI initiative starts with a business case. Few survive the gap between prototype and production.

The cost is not just the build. It is the domain experts, the maintenance, and the next project that starts from scratch.

time to valuetotal costroi clarity

04 complete traceability

Every decision points back to the passage that triggered it.

Expand any concept score to see the evidence behind it: the source document, the exact span, and the confidence attached. When a compliance audit asks why your AI acted, you have a documented, exact answer.

Q3 supplier review · page 4 of 12

supplier x — q3 review · pdf

Competitive landscape: our primary supplier shows signs of strategic retreat in key markets.

Following the Q2 incident, Supplier X is now contractually required to maintain a 14-day inventory buffer to prevent recurrence of the production line shutdowns.negative projection ·0.91
source documents
  • a9f3c1d2Supplier X — Q3 review
  • 7be04a91Amended supply terms
concept scores
negative projection0.91
obligation0.88
supplier dependency0.79
“…contractually required to maintain a 14-day inventory buffer…”

span 412–498 · confidence 0.95

expand evidence

05 concept-gated context

Context quality at every step. Precision that compounds.

A standard agent chain hands noisy context forward, so errors compound. ForgeAI gates the context every agent receives, so precision compounds instead.

standard chainnoisy contextprecision 0.80 → 0.33
  1. source
  2. no gate
  3. agent 10.80
  4. agent 20.64
  5. agent 30.51
  6. agent 40.41
  7. agent 50.33
forgeai chainconcept-gated contextprecision gated at every hop
  1. source
  2. forgeai gate
  3. compliancegated
  4. riskgated
  5. strategygated
  6. summarygated
  7. final outputcompound precision
agent dispatch
The orchestrator routes tasks based on concept activation, so each agent only sees the context it needs.
confidence signal
Concept scores are surfaced at every hop for retry and escalation logic.

06 governed queries

Governed queries that identify what is relevant, not what looks similar.

Compose five clause types into one precise query: optimisation, concepts, entities, modalities and time. Configure every query for recall, precision or a balanced approach. Every result is deterministic and auditable.

Findtheabout, framed as, in
  • optimisation
  • concept
  • entity
  • modality
  • temporality

07 agentic content acquisition

Agentic content acquisition from open sources.

Retrieve a single fact in seconds, or build an entire knowledge base in minutes. ForgeAI searches dynamically, each stage shaping the next, configured to your industry, your sources, your questions.

level 130 s

Forge-Lite

Targeted lookup, instant answers.

“Who is the CEO of Northgate Industries?”
one source · one pass
level 25 min

Forge-Search

Multi-source research on a topic.

“What are the key risks facing European logistics companies?”
several sources · one topic
level 315–60 min

Forge-Heavy

Deep research across sources and domains.

“Full due diligence on Northgate Industries covering ownership, financials, litigation, regulatory exposure, and press coverage.”
many sources · many domains

08 capabilities · the platform

Built on a platform you can see and run.

Governed queries, agentic content acquisition and the concept graph behind every score: how markers are forged, gated and run is on the platform page, live.

Governed queriesFive clause types in one precise query: optimisation, concept, entity, modality, time. Deterministic and auditable.the query wellAgentic content acquisitionForge-Lite, Forge-Search, Forge-Heavy: a single fact in seconds or a whole knowledge base in minutes, from open sources.the three levelsConcept graphSemantic Markers, variants, anchors, cues and issues as one navigable graph. Follow any link to its evidence.open the workspace
Use it with your own agentsyour documents

Wield AI with confidence.

Use ForgeAI instantly with your own agents. Unlock proofs of concept fast, and take them directly into production, with full ownership of your data.

your infrastructureyour taxonomyyour data stays yours
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