Narrow first, then wider
We start every agent on one workflow and prove it before giving it more to do. Wide agents fail quietly; narrow ones you can measure.
AI agents that do the work, not just talk about it
Backendz builds custom AI agents that read, decide and act across your CRM, ERP, inbox and databases. Each agent gets clear limits, a human sign-off for anything that matters, and a full log of what it did.
Or see how we engage first — four shapes, no sales call required.
- Agentic workflows
- Multi-agent systems
- Tool calling
- Human-in-the-loop approvals
- MCP servers
- CRM & ERP integration
- Email & inbox agents
- Document-reading agents
- Scheduling agents
- Guardrails
- Audit trails
- Role-based permissions
- Agent evaluation
- Cost per task tracking
- Private deployment
- 24/7 monitoring
No more retyping requests from email into the job system
Stop checking three systems to answer one customer question
Forget waiting days for a quote that takes minutes to assemble
Done with chasing missing documents the week before an audit
Skip building the same weekly report by hand
Say bye to automation that breaks when a message doesn't fit the template
Why choose Backendz for AI Agent Development?
Permissions before prompts
We decide what the agent can read, write and send before we write a line of its instructions. Least privilege, every time.
People sign off what matters
Refunds, payments, customer-facing messages: the agent prepares them, a person approves them.
Every action on the record
Each step the agent takes is logged with its reasoning, so you can check it, explain it and undo it.
We build AI Agent Development
Four ways this usually starts
Most enquiries land in one of these. If yours does not, say so on the call — we would rather shape the engagement than sell you the nearest shape we have.
Most teams start here
One workflow is eating your team's week
- We map one repetitive workflow end to end
- We build an agent for it and test it on past cases
- It runs supervised until the results hold
Best for: Teams who want proof before a bigger commitment
You need it running every day
- Production agent connected to your live systems
- Monitoring, alerts and cost-per-task reporting
- Ongoing tuning as your process changes
Best for: A proven workflow that needs to scale
Several systems, one process
- Multi-agent setup where each agent owns one part
- Hand-offs between agents and people, all logged
- Connectors built for systems without modern APIs
Best for: Operations that span CRM, ERP, email and job software
You want agents inside your product
- Agent features built into your SaaS or app
- Per-customer permissions and usage limits
- Cost controls that protect your margins
Best for: Software companies adding agentic features
Ideas that became systems in production
Every card is a build we shipped and still support. Open one for the decisions behind it.
We serve the best in the industry
All of it, written down
What falls inside this service. Nothing here is an upsell discovered later.
What our agents do
- Triage and route requests
- Create and update records
- Draft emails and replies
- Prepare quotes
- Chase documents and approvals
- Compile reports
- Book and reschedule
- Hand over to a person
What they connect to
- CRM
- ERP
- Email and calendars
- Job and ticketing systems
- Databases
- Internal APIs
- Document stores
- MCP servers for AI assistants
Keeping it safe
- Least-privilege access
- Approval steps
- Action logs
- Evaluation on past cases
- Confidence thresholds
- Rate and spend limits
Stack
- Claude and OpenAI models
- Model Context Protocol (MCP)
- LangGraph
- Python
- FastAPI
- .NET
- Node.js
- PostgreSQL
- Redis
- Hangfire
- Docker
- Azure
How it works
We document the task as it really runs, including the exceptions and the decisions only a person should make.
From the people who use it daily
Operations directors, CTOs and plant managers — the ones still using the system a year after the invoice cleared.
Freight operator · 14 depotsFreight operator · 14 depotsWe wanted answers our team could check against the original document. Having the relevant clause beside the response makes the assistant useful when reviewing policies and contracts.
Our rental journey had to work for both vehicle owners and travellers. Backendz brought listings, availability and bookings together into a platform that feels straightforward to use.
A single headcount does not tell us where congestion is developing. The zone-based view gives our team a clearer picture of how people are moving and where attention may be needed.
Tender preparation involves gathering evidence and getting the right people to review each section. Backendz brought those steps into one workspace, with drafts our team can check and approve.
Our estimating process needed to reflect how we actually price work. Backendz took time to understand the inputs and rules, then built a quoting journey our team could review and refine.
The team took time to understand how our staff work between appointments. The resulting system brings scheduling and client information together without making the day more complicated.
We could review working features throughout the build and give specific feedback. That made it easier to keep the product focused on the people using it.
Our field team needed access to job details away from the office. The mobile workflow keeps the relevant information close at hand and gives the office a clearer view of progress.
We wanted a client portal that reflected how we deliver our services. Backendz brought documents, requests and progress updates into a straightforward experience for clients and staff.
Our teams were entering the same information into several tools. Backendz mapped the process with us and built a more connected workflow with clear review points.
We needed scheduling, availability and shift changes in one place. Backendz shaped the system around the way our operations team works and stayed involved after launch to help us refine it.
Ask for references and we will put you on a call with the team that runs the system — not a case study PDF.
References available on request
We wanted a practical way to review PPE and safety-zone events using our existing cameras. The team focused on the situations our site managers need to investigate and made the footage easier to review.
The priority was a counting workflow our warehouse team could use during a normal shift. Backendz connected image-based counts with the records we already use and made discrepancies easier to review.
Our information was spread across several operational systems. Backendz designed a clearer way to ask questions, inspect the supporting evidence and keep approval with our team before an action is taken.
The reconciliation workflow gives our finance team one place to review mismatches and supporting records. We can trace an exception back to its source and decide what needs attention.
We had outgrown the spreadsheets that held our pricing rules. Backendz helped turn that knowledge into a quoting tool we can maintain and explain to new colleagues.
Connecting our sales and inventory systems was the priority. The integration gives our team a clearer view of updates and a practical way to investigate records that need review.
The cloud work started with understanding our existing systems and dependencies. The team documented the setup and gave us a clearer basis for monitoring and ongoing maintenance.
The engineers worked alongside our team and explained their decisions clearly. Code reviews and practical documentation helped us stay involved throughout delivery.
Why Backendz
5 yrs
In production
Ops CopilotTender Response DrafterPolicy & Contract AssistantPallet CountingConstruction Site PPE & Safety MonitoringCrowd Density MonitoringDigital Security PlannerVirtual EstimatorJoblogyPamacraftsRollBnBVenus AestheticsShiftTrackerFreight DispatchInvoice Reconciliation AIChilled TraceabilitySteel Quoting EngineFactory Floor AppFleet Driver App
We quote fixed and we hold it
2
Platforms run in-house
Agentic workflowsMulti-agent systemsTool callingHuman-in-the-loop approvalsMCP serversCRM & ERP integrationEmail & inbox agentsDocument-reading agents
Cloud Strategy & ArchitectureCloud MigrationCustom ERP DevelopmentInfrastructure ModernisationCloud EngineeringERP ImplementationCloudOpsERP IntegrationDevOpsSupport & Managed Cloud ServicesERP Customisation & ModulesCloud Cost OptimisationERP Data MigrationCloud Security & ComplianceAI & Edge InfrastructureERP Support & OptimisationSaaS Stack AuditCustom CRM DevelopmentCustom HR & Workforce ManagementCustom Job & Field Service ManagementCustom Client Portals & BookingSaaS Data Migration & ExitAI Proof of Concept & MVP
Scheduling agentsGuardrailsAudit trailsRole-based permissionsAgent evaluationCost per task trackingPrivate deployment24/7 monitoring
AI Agent DevelopmentCustom AI Assistants & ChatbotsGenerative AIAI Workflow AutomationNatural language processingCustom Software DevelopmentComputer Vision DevelopmentWeb App DevelopmentMobile App DevelopmentAI Video Analytics for CCTVProduct DevelopmentMVP DevelopmentUX/UI DesignApplication ModernisationSoftware Testing & QAMachine Learning & Predictive AnalyticsERP & operationsAI Product DevelopmentData & cloudProduct & designAutomation & integrationsSupport & operations
45
Services, one team
Senior engineers, not account managers
24/7 production support and monitoring
Still running on workarounds?
FAQ
The things people ask before they commit.
Still have questions?
Ask it on the call. We would rather answer an awkward question early than discover it in month three.
Book a callWhat is an AI agent?
An AI agent is software that takes a goal, decides the steps and carries them out across your systems: looking things up, updating records, sending messages and reporting back. Unlike a chatbot, which only answers questions, an agent finishes the job and hands over to a person when a decision needs one.
What is the difference between an AI agent and a chatbot?
A chatbot answers questions in a conversation. An AI agent takes actions to complete a goal, such as updating records, sending messages or creating jobs across several systems. Many businesses start with a chatbot and add agent capabilities once they trust its answers.
Are AI agents safe to connect to our systems?
They are when they are built with limits. Backendz gives each agent only the access it needs, requires human approval for sensitive actions, and logs every step, so you can see what it did, why, and undo it.
Which tasks suit AI agents best?
Tasks that are repetitive, mostly rule-based and spread across more than one system: handling service requests, chasing documents, preparing quotes and compiling reports. Work that needs judgement every time stays with people, with the agent preparing it.
Can AI agents work with our existing software?
Yes. Agents connect through APIs, databases, email and custom connectors. Backendz builds those connections as part of the project, including for older systems without modern APIs.
How long does it take to build an AI agent?
A focused agent for one workflow typically takes 4 to 8 weeks from mapping to supervised launch. Multi-agent systems across several platforms take longer.
What does an AI agent cost to run?
Running cost depends on task volume and the AI models used. We measure cost per task during testing, so you can compare it with doing the work manually before you go live.