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Use Cases

  • Bid Management
  • Compliance Questionnaire Response
  • DDQ Response
  • ESG Questionnaire Response
  • PQQ Response
  • Questionnaire Response
  • RFP Response
  • RFX Management
  • Reference Mapping
  • Security Questionnaire Response
  • Tender Management

Solutions

  • Bid Management Automation
  • Compliance Questionnaire Automation
  • DDQ Questionnaire Automation
  • ESG Questionnaire Automation
  • PQQ Questionnaire Automation
  • Questionnaire Automation
  • RFP Automation
  • RFX Automation
  • Reference Mapping Automation
  • Security Questionnaire Automation
  • Tender Response Automation

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  • SEQUESTO aOS
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  • Multi-Model Intelligence

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  3. Multi-Model Intelligence

LARGE-LANGUAGE MODELS

A stable frontier-model foundation for agentic commercial work.

SEQUESTO runs most work on one primary model family and upgrades deliberately to the latest capable release. The architecture can evolve as models improve, but the priority is stability, quality, and consistency for the teams working on top of it.

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Diagram of Multi-model Intelligence showing task-aware routing across multiple LLMs in the SEQUESTO aOS architecture
  • Adviscent
  • Barona
  • Delaware
  • Efficy
  • Eltel
  • ID Medical
  • ISS
  • Sligro

This layer is less about chasing providers and more about giving the rest of the platform a dependable intelligence foundation.

MODEL FOUNDATION

Stability before switching.

Most day-to-day work runs on one primary model family. That gives the platform predictable behaviour, cleaner evaluation loops, and less operational drift than constantly jumping between providers.

Multi-model architecture showing different LLMs routed to different tasks across the response workflow

FRONTIER QUALITY

Frontier class by design.

The chosen model layer has to perform where commercial teams feel it most: understanding long documents, following structure, using tools correctly, and maintaining quality through multi-step work.

Task-aware routing diagram showing different model types selected for parsing, retrieval, reasoning, and drafting tasks

AGENTIC EXECUTION

One foundation, many executions.

James and the sub-agents may take on different jobs, but most of that work still relies on the same underlying model family. The architecture can route special cases when needed without turning model choice into daily operational overhead.

Frontier-class model evaluation showing quality benchmarks across response work tasks

FUTURE-PROOF

Future-proof architecture.

The model market will keep moving. SEQUESTO absorbs that change at the platform layer so customer workflows, knowledge, and working habits do not need to be rebuilt every time the landscape shifts.

Future-proof architecture showing how the SEQUESTO aOS integrates new models as the model landscape evolves

RELATED LAYERS

See how the model foundation becomes usable work.

Agentic Harness

The Agentic Harness is the substrate behind how work gets executed in SEQUESTO aOS. It governs tool use, function calling, memory, reasoning, observability, and runtime safety so each task is assembled around the user’s request instead of pushed through one static chain.

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Agent Force

Agent Force is the specialist layer on top of the harness. James orchestrates the work, while specialist agents handle extraction, drafting support, review support, and document operations across tenders, questionnaires, and structured commercial work. The heavy lifting scales, but the final wording and approval stay human.

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Security & Governance

This layer is about proving what happened, controlling who can do what, and meeting enterprise security expectations without turning governance into a separate project. Traceability, usage visibility, access controls, SSO, ISO 27001, and SOC 2 Type II all support that goal.

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See the model layer in context.

Explore how the model foundation connects to the harness, specialist agents, and governed workflows inside SEQUESTO aOS.

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