Invoice exception handling
Extract invoice details, compare business rules and prepare exceptions for an authorized reviewer.
AI Squad/Computer vision
Turn visual signals into operational decisions.
A detection is only useful when it fits the camera, the environment and the decision someone needs to make.
Human specialistsOne accountable squadBuilt around your business
THE DELIVERY MODEL
Start with your ambitionBuild something that matters.
AI SquadPeople + process + AI tools
01Product02Design03AI04Engineering
WORKING TOWARDA product people can use
Your scope shapes the team, the plan and the release.
THE BUILD STUDIO
See the work behind the outcome.
Explore a delivery example: the people, the work and the decisions that turn a business need into useful software.
EXAMPLE DELIVERY PLANExplore the approach
Turn visual signals into operational decisions.
For manufacturing, logistics, construction, retail and site operations.
THE WORK
Review permitted footage, lighting, camera position and the operational decision.
Camera sample → detection target → evaluation plan
A HUMAN REVIEW POINTCan this view support the detection you need?
THE INTENDED OUTCOME
Plan a squad for thisA visual intelligence workflow with defined detection targets, measurable evaluation and a clear review-to-action path.
Illustrative delivery plan. Scope, integrations, team allocation and acceptance criteria are agreed for your project.
FROM A PLAN TO SOMETHING TANGIBLE
Work you can see. Decisions you can follow.
A shared backlog, regular reviews and clear delivery artifacts keep the engagement grounded in the product you are building.
Computer vision01
Camera, image and environment assessment
02
Detection targets and annotation plan
03
Model evaluation and threshold review
04
Human review and incident interface
05
Edge or cloud deployment design
06
Alert integrations and operating runbook
YOUR STARTING POINT
Bring the context. We will shape the next step.
Permitted footage representative of real conditions
The event or object you need to detect
Site constraints, connectivity and review responsibilities
You do not need every answer before speaking with us. Discovery can identify what is missing.
HUMAN EXPERTISE, BROUGHT TOGETHER
The right skills. Around the same table.
Explore our role coverage. A squad is shaped to your problem and stage; not every project needs every specialist.
A ROLE IN YOUR DELIVERY TEAM
AI Product Lead
Turns the business goal into a prioritized product roadmap.
Complementary expertise. Shared product direction.ONE CONNECTED DELIVERY JOURNEY
From the first question to what comes next.
No leap from a polished prototype to an unexplained launch. Every phase has a purpose, an output and a decision to make together.
- 01Product brief
Align
Agree the problem, users, decision owners and what success would mean.
- 02Prototype + architecture
Design
Map the experience, architecture, data, risks and first release.
- 03Working software
Build
Work through a shared backlog with regular demonstrations and decisions.
- 04Acceptance evidence
Validate
Test AI behavior, integrations and real user journeys in a controlled pilot.
- 05Release + runbook
Launch
Prepare deployment, permissions, monitoring, documentation and handover.
- 06Improvement roadmap
Evolve
Use feedback and agreed metrics to shape the next useful release.
START WHERE YOU ARE
A team model that fits your next move.
Choose the shape of the engagement. We will scope the roles, responsibilities and milestones with you.
A first product to launch
MVP squad
Deliver a coherent first product around a tightly prioritized scope and pilot users.
Discuss this engagementTeam, scope, price and schedule are agreed before work begins.THE FULL DELIVERY CAPABILITY
Beyond the AI model. Everything around it.
A useful product needs an experience, reliable data, connected systems and a way to operate it. Explore the capabilities we can bring into your scope.
01Product strategy
Discovery and workflow mapping
Use-case prioritization and feasibility
Business case and success measures
Roadmap, MVP scope and backlog
Stakeholder and delivery alignment
02Experience and design
User journeys and interactive prototypes
Web and mobile interfaces
Chat and voice experiences
Dashboards and admin workflows
Accessible design systems
03AI and agents
Model selection, routing and fallback
RAG, vector search and source grounding
Prompt design and version control
Agents, tool calling and orchestration
Voice, OCR and computer vision
AI output and retrieval evaluation
04Data and analytics
Data ingestion, cleaning and pipelines
Data models and quality checks
AI-ready knowledge sources
Business metrics and dashboards
Grounded summaries and analytics
05Software engineering
Frontend and backend development
APIs and database architecture
Authentication and authorization
User, tenant and role management
Product features and administration
06Business integrations
CRM, service and customer channels
ERP, finance, procurement and HR
Documents, knowledge and databases
Cameras, IoT and edge systems
Private APIs, legacy systems and blockchain
07Workflow automation
Event triggers and task routing
Extraction, classification and validation
Business rules and approval queues
Human escalation and exception recovery
Execution logs and system updates
08Security and governance
Access boundaries and role permissions
Audit, conversation and approval logs
Human review and action limits
Retention and environment controls
Prompt and model governance
09Testing and deployment
Software, workflow and integration testing
AI quality and performance evaluation
Cloud, private cloud and hybrid delivery
On-premise and edge deployment planning
Pilot rollout, release controls and runbooks
10Operate and improve
Usage, cost and latency monitoring
Product adoption and user feedback
Model, retrieval and workflow refinement
Operational documentation and handover
Scale planning and ongoing roadmaps
START WITH REAL WORK
Different industries. Concrete possibilities.
These are example opportunities to scope together, not customer results or prebuilt features. Choose the kind of work you want to improve.
A permission-aware knowledge desk
Help teams find approved policies, project knowledge and source-backed answers without crossing access boundaries.
Visual quality review
Evaluate product images for defined defects and present candidates with evidence for human inspection.
A connected guest service product
Bring guest requests, service coordination and a clear staff experience into one purpose-built application.
Property enquiry coordination
Build an agent that gathers requirements, checks approved information and prepares a viewing request for the team.
Claims document preparation
Classify incoming documents, identify missing information and route the case to a human claims reviewer.
Internal policy and procedure search
Help authorized staff locate operational guidance and referenced procedures within approved knowledge sources.
Loading and package review
Assess permitted camera views for agreed loading events, label checks and operational exceptions.
A field reporting command center
Connect site reports and project data into consistent progress views with traceable AI-assisted summaries.
Stock and store performance insight
Combine inventory, sales and service data into shared metrics and exception views for store operations.
A student service platform
Create a tailored portal that connects approved guidance, student requests and staff workflows.
Maintenance request coordination
Let a task-focused agent gather asset context and prepare work requests with human approval before execution.
ONE SQUAD. MANY POSSIBILITIES.
Find your starting point.
Start with a use case, then shape the product around your industry, users and systems.
Enterprise AI copilots
Turn company knowledge into answers people can use.
Custom AI agent systemsBuild agents that can take the next useful step.
AI workflow automationMove work forward. Keep people in control.
Data and AI analyticsGive every decision a clearer picture.
Custom AI product developmentYour product idea. A team to make it real.
Is AI Squad a team of people or autonomous AI employees?
AI Squad is a dedicated team of human product, design, AI and engineering specialists. The team uses AI tools and can build AI agents for your business. People remain accountable for delivery, review and decisions.
How is this different from hiring individual developers?
The engagement brings complementary skills around a shared product outcome, with product ownership, architecture, design, engineering and delivery coordination selected for your scope. You can also embed a squad alongside your existing team.
Do we need a complete specification to begin?
No. Bring the problem, the people it affects and any existing systems or constraints. A strategy or prototype engagement can establish feasibility, priorities and a scoped next step before a larger build.
Can you work with our current engineering team?
Yes. An embedded engagement can fit your repositories, tools and delivery practices. We agree responsibilities, interfaces and a review cadence so the squad adds capacity without creating another disconnected team.
Can you take a prototype into production?
Yes, after assessing what should be retained, rebuilt or tested. The plan can cover architecture, data, evaluations, access controls, reliability, deployment and the user experience around the AI capability.
What does a squad include?
The role mix depends on the problem and delivery stage. Our capability map covers product, architecture, design, AI, software, data, quality, operations and governance. It is a menu of expertise, not a promise that every engagement includes every role or a fixed headcount.
How are price and timelines agreed?
We scope the outcome, dependencies, team model and acceptance criteria with you, then propose an engagement. Timing and cost depend on that scope, data readiness, integrations and deployment requirements.
Can the product run in our environment?
Cloud, private cloud, hybrid, on-premise and edge approaches can be assessed during discovery. The appropriate architecture depends on your security requirements, model choices, operational constraints and available infrastructure.
Who owns the code and how does handover work?
Code ownership, licensing, repository access, documentation and handover responsibilities are agreed in the engagement contract before delivery begins. Raise any internal procurement or ownership requirements during the first discussion.
What happens after launch?
The next phase can be a handover, an ongoing product roadmap or a managed optimization engagement. Support coverage, response expectations and operational ownership are scoped explicitly rather than assumed.
BRING YOUR AMBITION
Let us build your next chapter.
Tell us what you want to build, improve or connect. We will help define a useful next step and the team to deliver it.
A conversation with our human teamNo complete specification needed