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AI systems your team can govern and operate.

Solvtify turns AI use cases into controlled production systems: data pipelines, integration points, review queues, access controls, and audit trails designed around real operating risk.

Production workflow Governed AI system
Live-ready
01
IngestDocuments, cameras, forms, and internal systems.
Validated
02
DecideModel output checked against business rules.
Controlled
03
ReviewHuman approval for exceptions and risk.
Audited
04
Write backApproved results posted to operating systems.
Integrated
ManagedQueue
AuditedLog trail
PrivateDemos
Capabilities
Vision · Documents · Agents
Deployment
Managed cloud
Controls
Review · Audit · Access
— 01 / Computer vision & ML

Vision systems that support real operations.

We design computer-vision workflows for capture, detection, review, and integration into business systems. Architecture is agreed during planning based on camera access, network constraints, data sensitivity, and operational requirements.

  • Inspection, counting, classification & defect detection
  • Camera and video-stream integration
  • Active learning & human-in-the-loop labelling
  • Model performance monitoring & drift detection
Inspection Counting Classification Camera integration Review queue Model monitoring
Computer visionInspection workflow
Reviewed
ReviewQueue
AuditTrace
IntegrateWorkflow
02 Where it works

AI examples by business need.

— 01

AI for MCST and property operations

Examples for resident requests, incident reports, contractor follow-up, maintenance records, and managing-agent workflows.

View examples →
— 02

AI for logistics documents

Examples for proof of delivery, delivery orders, shipment exceptions, vehicle photos, yard workflows, and system updates.

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— 03

AI for accident repair and surveyors

Examples for motor claims, vehicle damage photos, surveyor packs, repair documents, and evidence follow-up.

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— 04

AI document processing for claims

Examples for travel insurance, medical reimbursement, warranty claims, evidence extraction, validation rules, and review queues.

View examples →
— 05

AI agents for workflow automation

Examples for ITSM, finance, CRM, case updates, approval gates, and controlled multi-system actions.

View examples →
— 06

Enterprise AI knowledge assistant

Examples for HR policies, SOPs, product support, internal search, source references, and role-based answers.

View examples →
— 02 / Agentic AI

Automations with approvals, logs, and clear limits.

Agentic workflows are useful when the work is repetitive but still requires judgement. We build them as controlled automations with typed tools, approval gates, retry rules, and audit logs for every action.

  • Multi-step automations across internal systems & M365
  • Tool / function calling with strict typed schemas
  • Approval gates, retry policies, and idempotency built in
  • Full audit log: prompt, tool calls, decisions, outcomes
Approval gates Tool controls Case updates Audit log Human review Retry rules
Agentic workflowApproval-controlled automation
Audit on
Check supplier recordCRM + finance system
Allowed
Draft responsePolicy-matched template
Queued
Update case statusRequires human approval
Review
Write audit eventPrompt, tool calls, result
Logged
ControlledTools
HumanApproval
CompleteAudit trail
— 03 / Document intelligence

Structured data out of unstructured paperwork.

Forms, invoices, statements, contracts, the documents that move work through your organisation are also where it gets stuck. We build extraction pipelines that produce structured, validated, audit-trail-bearing records the rest of your systems can act on.

  • OCR and LLM-assisted pipelines for high-variability formats
  • Confidence scoring & review queue routing
  • Field-level validation tied to your business rules
  • Direct write-back to ERPs, CRMs, and case systems
Document extraction Confidence scoring Review queue Validation rules System write-back
Document intelligenceExtraction and review queue
Validated
VendorVerified
AmountMatched
ExceptionNeeds review
RulesValidation
ReviewQueue
ExportControlled
03 How we deliver AI

Four principles for production AI.

— Principle 01

Start with the system, not the model.

A great model in a bad system is unusable. We design the data flow, integration points, and human review surfaces first, then choose the model.

— Principle 02

Keep the model replaceable.

Models change quickly. We design the application so the underlying model can be changed without rebuilding the full workflow.

— Principle 03

Audit every decision.

Inputs, prompts, tool calls, outputs, and human overrides are all logged. AI does not get a special exemption from our audit standards.

— Principle 04

Design for data governance.

AI systems are operated within Solvtify-managed infrastructure by default. Where stricter requirements apply, isolation strategy, retention policy, access controls, and deployment architecture are discussed during planning.

04 Frequently asked

What clients ask us before signing.

What kind of AI projects does Solvtify take on?+
Solvtify develops practical AI and agentic AI systems for automation, operational efficiency, decision support, and workflow improvement.

Have an AI workflow worth testing?

Tell us the decision, the data, and the operational risk. We will help identify what should be automated, what needs review, and what should stay manual.

Discuss a project→ See the platform