multi-tenantstandard
Managed multi-tenant
ForgeAI runs in our AWS environment, with full per-customer isolation.
forTeams that want the fastest time to deployment with standard enterprise security.
enterprise ai · deployment · security · economics
The control layer for enterprise AI in production.
ForgeAI sits between your data and your decisions. Every input passes through the Semantic Control Layer; every output is governed, explainable and ready for the agents and workflows you already run. In your environment, from day one.
Your data — Your decisions
01 inputs & sources
Document ingestion pipelinespdf · doc · csv · xls
Vector stores & data lakesembeddings · retrieval
Agentic searchapi · dsl
Prompt workflowsf(x) · { }
02 forgeai semantic control layer
Retrieval layerconcept-gated context · governed queries
Semantic marker layer
basegeneral & regulatorybusinessindustry semanticscustomyour taxonomy
calibrated score on every passage · 0.86 supply_chain_disruptionOutput validation layerpass
03 governed outcomes
Your agentsorchestration frameworks · live on day 1
LLM & embedding providersclient-selected · governed regardless
Workflow automationorchestration · automated actions
Operational dashboardsdata & decision intelligence
API, integrations & monitoringconnect to existing systems · audit feed
01 your agents · day one
Use it instantly with your own agents.
01Your agents call the control layer over the API. Context is gated on the way in; outputs are scored and vetoed on the way out.
02Your providers stay. Choose your own LLM and embedding providers; ForgeAI governs the workflow regardless of provider.
03Your documents stay yours. Your infrastructure, your taxonomy, your keys. Full ownership of your data at every stage.
Time to productiontwo paths
internal path · build yourself6–18 months
domain expertspipeline codeannotation toolsevaluation harness
forgeai path · connect your agentsinstant
semantic markers · calibratedyour own agentsaudit trail on
Live on day one, not in a quarter.
No experts to hire, no annotation tooling to build, no pipeline code to maintain. The control layer is already trained, calibrated and audited; your agents simply start using it, on your own documents.
02 deployment options
Deploy where your data lives.
Regulated industries, data-residency requirements and sovereign deployments all demand control over where compute runs and where data rests. Four options, one control layer.
single-tenantenterprise tier
Managed single-tenant
Dedicated infrastructure for your deployment, with a single-tenant application data store.
forTeams with strict data-isolation requirements or specific compliance constraints.
your keysenterprise tier
Client-managed encryption
Client-managed KMS for the VM and application runtime, client-managed encryption keys for the data store, HSM-backed handling where required.
forRegulated industries and security-conscious teams who require key sovereignty.
your providersany tier
Client-selected AI providers
Choose your own LLM and embedding providers. ForgeAI governs the workflow regardless of provider.
forTeams with existing AI-provider relationships or model preferences.
03 security & compliance
Built to pass your security review.
Designed to answer the questions your security team will ask before approving any AI vendor, and to satisfy the EU AI Act's transparency and audit-trail requirements by design, not by retrofit.
security review · checklistwhat your team will ask
tenancy
Tenancy isolation
Per-customer isolation at the infrastructure level. Managed single-tenant deployments for teams with strict data-separation requirements.
key management
Client-managed KMS
Client-managed Key Management Service for the VM and application runtime. You control the keys; ForgeAI operates within them.
encryption
Client-managed encryption keys
Client-managed encryption keys for the application data store. HSM-backed key handling where required.
identity
Authentication integration
SSO via SAML and OIDC. Role-based access control with separation of control plane and data plane.
infrastructure
AWS-native infrastructure
Native security controls, VPC isolation, encryption at rest (AES-256) and in transit (TLS 1.3). No third-party infrastructure dependencies.
audit
Audit and traceability
Every classification logged. Every output traceable to source, concept and reasoning chain. A full audit trail designed for regulatory defensibility.
04 economics · relevance, not volume
Same model. Different system.
One configuration layer turns a horizontal model into a governed vertical solution. The model core stays what it is — GPT, Claude or Gemini — but it only ever sees the text that matters: scored and filtered before inference, validated and explained after it.
One model core, two different systemsaverage token reduction 87 %
without semantic markershorizontal model
documents
→100 % of the textmodel coreGPT · Claude · Gemini
↳ what comes out
generic answer
no traceability
no comparative view
with semantic markersgoverned vertical solution
documents
→semantic markersScore & filter
→13 % of the textmodel coreGPT · Claude · Gemini
→semantic markersValidate & explain
↳ what comes out
calibrated & verified
governance
contextual insights
04 economics · cost at scale
The cost curve flattens as you scale.
Standard per-search pricing applies to most deployments. ForgeAI's optimisation and distillation layer then creates lighter, purpose-trained models from your usage patterns, replacing full-inference searches with a materially lower cost per search as usage grows.
detailed cost modelling is provided during enterprise sales conversations
Cost curve at scaleper search
cumulative costannual content acquisition spend
standard per-search costwith model distillation
distillation viablereduced unit cost ↘05 across industries
Designed for the enterprises that need governed AI.
ForgeAI applies across verticals while remaining specifically configurable to each one: your taxonomy, your thresholds, your evidence.
financial services
Counterparty risk and AML/KYC alert enhancement
Track risk signals across earnings calls, filings, news and supplier disclosures. Reduce false-positive alert volume with calibrated precision: suppress benign language without sacrificing genuine risk-signal recall.
counterparty riskaml / kycfull audit trail
legal & compliance
M&A due-diligence screening
Point at a target company and receive a briefing-ready risk profile: signals sourced, classified by severity and traceable to evidence. The highest-risk documents reach the deal team and advisors first.
due diligencepriority review queueseverity
pharmaceutical
Drug safety and regulatory intelligence
Classify adverse-event signals, extract regulatory obligations and structure clinical evidence across submissions and safety literature.
adverse eventsobligationsclinical evidence
ai safety & governance
Input and output classification
Classify prompts, retrieved context and model responses against your policy, with a full audit trail on every decision your agents make.
prompt policycontext gatingoutput veto
06 outcomes & engagement
24h
go / no-go decision
Bring your data. Automated discovery and agentic concept detection run against it on the spot.
10×
efficiency & reliability
Improvement in the efficiency and reliability of generative AI outputs under the control layer.
1schema
shared across every team
New teams inherit the core configuration and customise from there. Expansion is incremental, not a rebuild.
Ready for enterprise scale?discovery in 24 h
Bring your data. Bring your agents.
We'll cover deployment, security and how ForgeAI fits your environment, then connect your first agents. Discovery starts in 24 hours; the proof of concept goes directly into production.
your environmentyour keysyour providersyour data stays yours