GUARDRAILS OS Talk to us
Guardrails OS · Agent operating system

An operating system for defensible AI in regulated work.

Persistence. Traceability. Privacy. Policy Control.

Guardrails OS is the moat and the method. It lets a firm build and deploy new AI agents on customer proprietary workflows in weeks, with the privacy, accuracy, and auditability that enterprises require. Each new agent inherits the same trust foundation.

See the architecture Reporting scope
  • 12 Weeks to production agents
  • 4 Trust pillars
Reused vs newly built

Why each new vertical agent launches faster and costs less.

Guardrails OS is the shared foundation that every new AI agent inherits. Firms only build what is truly vertical-specific on top. The result: lower cost, faster launch, higher leverage on every subsequent agent.

Reused

Guardrails OS infrastructure
Data ingestion
Identity and privacy
Ontology
Rules engine
Model orchestration
Audit trail
Human review
Output generation

Built once. Inherited by every new agent.

Newly built

What is created for each new vertical
  • Domain ontology
  • Regulatory rules
  • Workflow templates
  • Domain-specific integrations
  • Go-to-market expertise

Vertical-specific build. Small, focused, fast.

Lower cost

Shared infrastructure amortized across every new agent.

Faster launch

New agents reach production in weeks, not quarters.

Higher leverage

Every new agent compounds the platform's value.

Guardrails architecture

Eight components. One governed AI platform.

The Guardrails OS foundation carries data ingestion through signed, defensible outputs. Every layer is instrumented for audit and permissioned by role.

01

Data fusion engine

Ingest and unify files, systems, sensors, images, and APIs into a single evidence graph.

02

Dynamic ontology builder

Domain knowledge modeling and relationships across data and workflows.

03

Knowledge and rules layer

Business rules, regulatory logic, thresholds, and validation enforced before generation.

04

Adaptive orchestration

Multi-model routing, tools, connectors, and execution sequencing tuned per workflow.

05

Query-to-action loop

Requests become actions, actions produce evidence, evidence closes the loop back into the ontology.

06

Stateful AI agents

Long-running, permissioned agents that hold context across sessions, review checkpoints, and delivery.

07

Traceable outputs

Every claim carries a link to the source evidence. Change the source, regenerate the output.

08

Assistive outputs

Drafts, dashboards, and signature-ready reports handed to the licensed professional for review and sign-off.

Agent controls

Four controls the platform enforces before any output ships.

Accuracy

Schema checks, unit normalization, criteria validation.

Outputs are validated against the schema, units are normalized to canonical form, and every value is checked against regulatory criteria before an agent is allowed to write.

  • Schema and type enforcement
  • Unit conversion and normalization
  • Criteria and threshold validation
Auditability

Click-to-source traceability to original evidence.

Every number, sentence, and diagram is linked back to the source document, sensor, or system of record. Reviewers click a claim and read the evidence that produced it.

  • Full evidence lineage
  • Immutable versioning
  • Replayable agent runs
Privacy

Your data and IT remain in place. Role-based access.

Customer data stays on customer infrastructure. Access is enforced by role. Customer content is never used to train models.

  • In-place data, in-tenant compute
  • Least-privilege access controls
  • Encryption in transit and at rest
Model routing

Select reasoning, math, and imaging models by cost, performance, jurisdiction, or application domain.

Policy-driven multi-model orchestration. The right model for the right step, with jurisdictional and cost constraints enforced by the platform.

  • Reasoning, math, imaging, retrieval
  • Cost, latency, and jurisdiction budgets
  • Domain-tuned routing policies
Guardrails OS reporting scope by agent type

Where regulated reporting eats professional time.

Estimated share of professional-service effort attributable to regulated reporting, evidence assembly, QA and QC, compliance, and submission production. Sectors at the top of the chart are the highest-leverage places to deploy a Guardrails OS agent.

  1. Life sciences · regulatory dossiers60%
  2. Medical devices · regulatory submissions55%
  3. Life sciences · deviation, CAPA, validation55%
  4. Phase II ESA50%
  5. Crop protection · product registration50%
  6. Nuclear · compliance and license reporting48%
  7. Medical devices · CAPA and post-market45%
  8. Aviation · airworthiness and maintenance42%
  9. Phase I ESA40%
  10. Crop protection · study and evidence38%
  11. Oil and gas · integrity and environmental35%
  12. PFAS and contaminated sites35%
  13. Food and ag · FSMA, HACCP, recall32%
  14. Aerospace and defense · quality and cert30%
  15. Remediation28%
  16. Construction · hazmat, lead, asbestos25%
  17. Rail · safety and incident25%
  18. Critical manufacturing · quality and CAPA24%
  19. Air emissions and permitting22%
  20. Hazardous waste20%
  21. Landfill and solid waste18%
  22. Industrial EHS compliance18%
  23. Water and wastewater16%
  24. Rail · asset compliance16%
  25. Construction · materials, QA and QC15%
  26. Construction · SWPPP and stormwater12%
  27. Construction · permit and closeout12%
  28. Industrial · asset integrity10%
  29. Construction · daily reports8%
Reporting workload percentage. Higher percentages mean more professional labor becomes reports and submissions, and more of that labor is a candidate for a Guardrails OS agent.
Regulated industry sector map

One governed evidence-to-report platform. Many vertical businesses.

Guardrails OS is built once, then extended into three families of regulated work. Each vertical becomes a Remedient-style brand with its own agents and its own customers, sharing the same trust layer underneath.

Built environment and infrastructure

Proven
Environmental
ESA · PFAS · air · water · waste · remediation
Construction
SWPPP · dewatering · hazmat · safety · closeout
Transportation and rail
NEPA · ROW permits · inspection · rail safety
Energy and utilities
Siting · grid compliance · commissioning
Water infrastructure
NPDES and DMR · drinking water · asset closeout
Mining and natural resources
Reclamation · tailings · MSHA
Facilities and data centers
Commissioning · EHS · water and energy reporting

Manufactured and regulated products

Adjacent
Chemicals and crop protection
Dossiers · SDS · TSCA, REACH, FIFRA
Life sciences and pharma
CMC dossiers · validation · deviation and CAPA
Medical devices and diagnostics
510(k) and PMA · technical files · post-market
Food and ag manufacturing
FSMA · HACCP · recalls · supplier compliance
Critical manufacturing
Quality · inspection · maintenance · CAPA
Aerospace and defense
Airworthiness · quality · test evidence

Regulated operations

Expansion
Industrial EHS
Site EHS · air, water, waste · certifications
Oil and gas · midstream and LNG
Integrity · methane · spill and leak · closure
Aviation operations
Maintenance · inspection · occurrence records
Nuclear
Inspection · corrective action · license reports
Utility operations
Vegetation · spill · wildlife · permit reporting
Facility operations
Inspection · water safety · compliance rollups
One trust foundation Many defensible agents
Ranking agents

How to choose agents.

Six criteria to use when you are deciding which of your enterprise workflows are the best candidate for automation:

  1. 01

    Documentation intensity

    What share of professional labor becomes reports and submissions in this workflow. The higher the share, the more compressible with an agent.

  2. 02

    Report frequency

    Daily, weekly, and monthly recurring work compounds faster than occasional work.

  3. 03

    Cost of error

    Regulatory, financial, safety, or license consequences of a mistake. The higher the cost, the more valuable accuracy and traceability become.

  4. 04

    Evidence complexity

    Number and heterogeneity of source systems and documents an expert must reconcile. High complexity favors the data fusion engine.

  5. 05

    Standardization

    Enough repeatability across customers that the same agent can serve many buyers with only light configuration.

  6. 06

    Required professional accountability

    PE, QEP, regulatory affairs, QA, authorized inspector, physician, or scientist. Human sign-off is the point, not a workaround.

The company

Guardrails OS is a product of AGBLOX.

AGBLOX owns the patents and software and builds the vertical AI agents. Guardrails OS is how those agents become defensible in the enterprise. Remedient is the agent that performs the work, all as a service.

Visit AGBLOX.com See Remedient