Safety evaluation
Red teaming, adversarial testing, failure mode analysis and evaluation design for models, agents and retrieval systems, before release and after it.
AI safety·Policy·Engineering
Applied AI capability,held to a standardyour organisation can defend.
SSTech Advisory brings AI safety, policy and engineering together: evaluating how systems can fail, setting the policies and controls that keep them accountable, and building them to that standard.
Governed delivery surfaceReady
01IntakeReceived
02OrchestrationRouted
03EvaluationMeasured
04JudgementHuman
05AuthorityBounded
06ExecutionControlled
07RecordKept
Solution capability, shown as a pattern
01 / Position
We do not begin with the model.
We begin with the decision, the workflow, the evidence, the constraints and the authority involved. The model is one component of the resulting system, and it is chosen once the rest of the system is understood.
- 01DecisionStarting point
- 02EvidenceWhat is known
- 03ArchitectureHow it holds
- 04AIOne component
- 05EvaluationMeasured
- 06AuthorityWho decides
- 07OperationRun and owned
02 / AI safety and policy
Safety and policy are where we start, not where we finish.
We help organisations understand how an AI system can fail, what it must never be allowed to do, and which policies and controls keep it accountable. Technical evaluation and policy work are carried out together, so each one informs the other.
AI policy and governance
Organisational AI policies, acceptable use standards, risk registers and decision rights, written so that the people bound by them can follow them.
Regulatory alignment
Mapping systems against relevant frameworks and emerging regulation, identifying the gaps and setting out what would close them.
Policy and leadership briefings
Clear technical briefings on AI capability, risk and safety for boards, policy teams and public bodies who have to decide what to permit.
Reference frameworks
- EU AI Act
- NIST AI RMF
- ISO/IEC 42001
- OECD AI Principles
- UK AI regulation principles
Frameworks are referenced to structure the work. We do not certify, accredit, guarantee compliance or provide legal advice.
Our approach to AI safety03 / Delivery sequence
A working model is not yet a capability your organisation can run.
Five stages, in order. Each one has to be satisfied before the next is worth starting, and each produces something your team can inspect.
- 01ScopeAdvise
The decision or process in question, described precisely enough to design against. Where it sits, who owns it, and what a wrong answer costs.
Produces Written problem definition - 02DesignAdvise
Architecture, data path and integration points set out before any build begins, together with the tests the finished system will have to pass.
Produces Architecture and test criteria - 03BuildBuild
Working software developed against those tests rather than towards a demonstration, with evaluation running alongside the build from the start.
Produces Working software and results - 04ControlBuild
The limits on what the system may decide alone, the review points where a person is required, and the escalation route when confidence is low.
Produces Authority and escalation model - 05HandoverEnable
Documentation, training and an operating routine your own team can carry without us, so the capability stays in the organisation.
Produces Operating routine and ownership
04 / Operating model
One system, three states.
Advise, build and enable are not separate services. They are the same system at three points in its life. Select a state: the structure carries forward rather than starting again.
Decide what deserves to be built, and under what conditions.
Senior technology judgement applied before commitment: AI and technology strategy, opportunity assessment, enterprise architecture, cybersecurity and technology risk, build versus buy, operating model design and implementation planning.
- 01AI and technology strategy
- 02Opportunity assessment and prioritisation
- 03Enterprise architecture and build versus buy
- 04Cybersecurity and technology risk
- 05Technical governance and operating model
Build against operating requirements rather than demo criteria.
The decision architecture stays in place and expands into working software: evidence aware knowledge systems, intelligent automation, controlled AI workflows, integration, evaluation infrastructure, deployment and release control.
- 01Evidence aware retrieval and document intelligence
- 02Agentic workflows, orchestration and tool use
- 03Integration, permissions and privacy aware architecture
- 04Evaluation harnesses, monitoring and observability
- 05Deployment, release control and rollback
Leave capability behind, not dependency.
The completed system extends outward into the organisation: technical handover, operational readiness, governance structures, evaluation methods, documentation, operating procedures and technical leadership guidance.
- 01Technical handover and operational readiness
- 02Governance structures and review cadence
- 03Documentation, playbooks and runbooks
- 04Professional workshops and technical briefings
- 05Implementation support and technical mentoring
System state A / DecisionB / SystemC / Organisation
Inputs weighedComponents assembledExtended outward into
Business objective
Existing systems
Constraints
Risk
Organisation
Data
Integration
Retrieval
Models
Orchestration
Evaluation
Controls
Operating interface
People
Ownership
Monitoring
Documentation
Processes
Evaluation methods
Resolves to
Decision architectureWorking technical capabilityOperational organisational capability
What will be built, in what order, under which controls, and what will be left alone.
Software running in your environment, with its tests, evaluation results and limits documented alongside it.
A team that can operate, question and extend the system, working from documentation written for them.
Six inputs converge through judgement into one decision architecture.Data and controls carry forward; the architecture expands into eight components.Controls stay owned; the system extends until the organisation can run it.
05 / Solution capabilities
Five capability families, each with a working shape.
Most engagements draw on more than one. They are set out separately so the shape of each is clear, and each pattern is one we advise on, architect and build.
AI strategy and architectureAI readiness, opportunity prioritisation, enterprise architecture, transformation planning, build versus buy decisions and implementation roadmaps.
Inputs → Priorities → Decision → Architecture
Enterprise AI and knowledge systemsEvidence aware retrieval, document intelligence, organisational knowledge workflows and AI assisted decision systems.
Sources → Retrieval → Evidence → Provenance
Intelligent automation and agentic systemsControlled multi stage workflows, tool enabled automation, orchestration, approval boundaries and bounded execution.
Intent → Orchestration → Authority → Tool → Record
AI security, evaluation and reliabilityCybersecurity thinking, evaluation harnesses, retrieval testing, adversarial assessment, evidence verification, permissions, privacy and release criteria.
System → Test → Failure → Control → Re-test
Research to product and technical advisoryTechnical feasibility, architecture, evaluation and engineering pathways for translating research and prototypes into usable systems.
Prototype → Evaluation → Engineering → Operating system
Presented as solution capability. These are systems we design and build, described honestly as capability rather than as completed client deployments.
All eleven solution categories06 / System architecture
Assembled in layers, each one accountable.
Select a layer to isolate it and see what it depends on. This is the shape of a solution capability, not a record of a deployment.
06Operating interfaceWhere people meet the system, see its confidence and take the decision it defers to themSurfaces 05
05Governance controlsAuthority limits, approval routing, escalation thresholds and the record each decision leaves behindBounds 03, 04
04Evaluation harnessTest sets, scoring and live monitoring that keep working once the system meets real conditionsObserves 03
03Model and orchestrationRetrieval, tool use and routing across steps, chosen for the task rather than for noveltyDepends on 01, 02
02Integration surfaceConnections into the systems your organisation already runs, with permissions carried through intactDepends on 01
01Data foundationSources, quality, lineage and access rules established before anything is built on top of themBase layer
07 / Control
Three conditions decide whether a system acts alone.
Switch a condition off and the route through the gate changes. In our engagements this is designed with you before build, not attached afterwards.
Conditions
Route ClearedHeld
GateControlled executionHuman decision
- Bounded execution
- Action recorded against scope
- Execution suspended
- Escalation to accountable role
- Decision taken by a person
Approved for controlled executionHeld for a person to decide
The system may act inside the scope agreed, and every action it takes is recorded against that scope.
Decision recordWritten either way
Solution capability. Not a certification, an accreditation or a statement of legal compliance. How we approach responsible AI.
08 / Engagement pathways
Choose the entry point that matches where you are.
Each pathway is an example engagement shape. Phases and their proportions are agreed with you, and no duration is fixed before scope is understood.
DiagnosticExample engagement
ScopeThe decision, its owner and the cost of getting it wrong.
AssessmentData, systems and organisational readiness examined together.
FindingsWhat holds, what does not, and what remains unresolved.
RecommendationA defensible next step, sized and sequenced.
Ends with a written position and a recommendation you can take to a board, whether or not it says proceed.
Discuss this pathwayBuild partnershipExample engagement
ScopeAgreed problem definition and success tests.
DesignArchitecture, data path and control design settled first.
BuildDevelopment against the tests, with evaluation running alongside.
ControlAuthority limits, review points and escalation put in place.
HandoverDocumentation, training and an operating routine.
Ends with software running in your environment, its limits documented and its controls agreed before launch.
Discuss this pathwayCapability programmeExample engagement
BaselineCurrent practice, tooling and confidence assessed honestly.
ProgrammePractical sessions built on your own systems and cases.
PracticeSupported application to live work, with mentoring.
ReviewWhat stuck, what needs reinforcing, what to adjust.
Ends with your team operating and questioning the system without us, and a review point set for later.
Discuss this pathway09 / Context
Where a wrong answer is expensive.
Our approach is designed for environments where technical decisions carry material consequences and somebody has to be able to explain how one was reached.
01Healthcare and life sciencesSupport for qualified professionals. We do not diagnose, treat or replace clinical judgement.
02Financial systemsDecisions that have to be explained to a customer, an auditor or a regulator.
03Cybersecurity and technology operationsThreat classification and response where automated authority has to stay bounded.
04Enterprise operationsOperational systems where an error propagates before anyone notices.
05Research and higher educationTechnical collaboration on applied problems. No results or publications are promised.
06Public and regulated environmentsServices where fairness and continuity matter as much as efficiency.
10 / Capability development
People decide whether a system is adopted or abandoned.
Training is scoped to the audience and the stage the organisation has reached, from an executive briefing before investment to handover training after a solution is delivered.
Executive briefing
60 to 90 minutes on opportunity, risk, governance and sequencing for the people making the investment decision.
Professional workshop
Half or full day on responsible use, confidentiality, verification and appropriate professional application.
Technical masterclass
Hands-on development of retrieval, agentic and evaluation practice using your own stack and constraints.
Solution handover
Documentation, user guidance and adoption training so the organisation can operate what has been built.
Our programmes are professional training. They are not accredited or certified courses, and no certificates are issued on behalf of any awarding body.
Request a training programmeA serious AI initiative usually starts with a conversation.
Bring us the decision you cannot afford to get wrong.
We can help determine whether AI belongs in it, what should be built, how it should be evaluated, what controls it requires and where human authority should remain.
Details
Enquiriesinfo@sstechadvisory.com
What to send
The decision or process in question, who owns it, and what makes it difficult. Technical detail is welcome but not required.
Working reach
Online with organisations internationally, and on site in Islamabad and Lahore where an engagement requires it.