Dasher Consulting Intelligence Framework

Dasher Consulting Intelligence Demonstrator

We help companies reuse their historic tender knowledge to produce better estimates, expose risks earlier and make bid/no-bid decisions with evidence.

This demonstrator shows how agentic AI can process tender documents, compare historic projects, identify risks, surface estimating questions and prepare evidence-backed recommendations.

Agents can search the tender pack, compare historic jobs, check skill guidance, flag missing clarifications and prepare a recommendation while showing the evidence used.
Primary demo caseHospital ward refurbishment tender reviewNorthbridge Clinical Engineering Ltd · Healthcare engineering, refurbishment and live environment construction

A UK engineering contractor bidding for hospital refurbishments, theatre upgrades, laboratory fit-outs and framework works in live restricted estates.

Other sector examples
01Tender pack in
02Historic evidence retrieved
03Risks and estimates analysed
04Board-ready recommendation

Dasher Consulting Tender Intelligence

Live hospital ward refurbishment review

Evidence-led tender review
Generated recommendationHigh confidence

The ward tender is commercially credible but should not move to final price until access windows, decant responsibility and infection-control ownership are clarified. Comparable projects show margin pressure when productivity assumptions were accepted too early.

Risk confidence is high because the brief, requirements, risk register and clarification log agree on the main risk themes.

HighRestricted access and labour productivity

The programme limits noisy work and leaves access windows ambiguous, which can erode labour productivity.

HighDecant and stakeholder sign-off

The clarification log shows decant responsibility and approval paths are still open.

MediumInfection-control preliminaries

Barriers, cleaning regime and failed-inspection ownership need to be priced as real constraints.

MediumSupplier and commissioning evidence

Historic records point to ventilation and commissioning documentation as common late-phase issues.

Proceed to board review as a conditional bid. Hold price freeze until the open clarifications are answered or include explicit risk allowances tied to access, decanting and infection-control constraints.

Submitted tender pack

Hospital ward refurbishment

Indexed source preview

Hospital Ward Refurbishment Risk Register (CSV)

Risk register
Hospital_Ward_Refurbishment_Risk_Register.csvPage 1

Hospital Ward Refurbishment Risk Register

Initial risks include late decant approval, estates access delays, infection-control inspections, long-lead ventilation components and stakeholder change requests.

Indexed risk tags: risk, infection-control, stakeholder-signoff.

Security classification: Internal. Department owner: Commercial.

DOC-TDR-005 · knowledge-base/opportunities/hospital-ward-refurbishment/ · synthetic original preview page 1 of 2
Hospital_Ward_Refurbishment_Risk_Register.csvPage 2

Hospital Ward Refurbishment Risk Register - evidence appendix 2

Initial risks include late decant approval, estates access delays, infection-control inspections, long-lead ventilation components and stakeholder change requests.

Related metadata: PRJ-2025-011, CUS-003, EMP-035, EMP-003.

Searchable terms include access, decanting, commercial, risk, bid, recommendation, capacity, risk.

DOC-TDR-005 · knowledge-base/opportunities/hospital-ward-refurbishment/ · synthetic original preview page 2 of 2

Dasher Consulting Knowledge Engine

Skills, lessons and commercial rules

Dasher Consulting Company Intelligence

Leadership pressure points

Comparable history

Projects retrieved for context

Capacity and skills

Delivery constraints

Trust layer

Evaluation and trace view

Azure architecture

Production-shaped, cost-controlled foundation

Foundry observability pattern

Trace for the selected answer

Your data stays in your Azure subscription

The demonstrator is synthetic, but the architecture is shaped around source evidence, managed identity, access-aware metadata, evaluations and low-cost Azure services.

Blob StorageAI Search BasicFoundry evaluationsREST API