Backend
- Java
- Spring Boot
- REST APIs
- Microservices
AI Agent Solutions
Agentic workflows that carry out real business tasks, not chatbots that answer questions about them.
Overview
Most AI projects inside businesses stall at the same point. A model that can answer questions is interesting for a fortnight, then nobody opens it again, because answering was never the bottleneck. The bottleneck was the work itself: the twelve-step process someone repeats forty times a week across four different systems.
Agentic workflows target that work directly. An agent is given a goal, a defined set of tools it is allowed to use, and rules about what it must not do on its own. It then plans the steps, calls the systems, handles the results, and either completes the task or escalates to a person with everything already assembled.
The engineering that makes this work is mostly not model work. It is integration, permissions, state handling, retries, logging, and knowing exactly where a human has to sign off — which is the same discipline as any other enterprise system, applied to a component that behaves probabilistically.
We are deliberate about scope. Agents are worth building where a process is repetitive, rule-heavy, spans multiple systems, and has a checkable output. Where a task needs judgement that carries real consequences, we build the agent to prepare the work and stop, leaving the decision with the person accountable for it.
What we deliver
The concrete outputs of an engagement in this area.
Process assessment
An honest read on which of your processes suit an agent and which do not, before anything is built.
Agent and workflow design
The goal, the permitted tools, the step boundaries, and the escalation rules written down and agreed.
Tool and system integration
The agent connected to your real systems over REST and third-party APIs, with scoped credentials rather than blanket access.
Human approval gates
Defined points where work pauses for sign-off, so nothing irreversible happens without a person authorising it.
Guardrails and constraints
Input validation, output checking, spend and rate limits, and explicit blocks on actions the agent must never take.
Audit logging
A record of what the agent did, which tools it called, and what it produced — reviewable after the fact.
Evaluation and monitoring
Test cases the workflow is measured against before release, and monitoring that flags drift or failure once it is live.
Handover and training
Documentation and sessions so your team can supervise, adjust, and extend the workflow without us.
Technologies we use
The parts of our stack that apply to this work.
Integration
- REST APIs
- Third-party APIs
- ERP / PMS
- Enterprise systems
Databases
- PostgreSQL
- MySQL
- NoSQL
Cloud & infrastructure
- AWS
- Microsoft Azure
- Security
- Monitoring
Our process for this work
The seven phases applied specifically to ai agent solutions engagements.
01
Requirement analysis
We map the business problem, the people affected by it, and the technical constraints before a line of code is written.
02
Solution architecture
We define the system structure, data model, integrations, and hosting approach so the build scales past its first release.
03
UI/UX design
Screens and flows are designed around how the work actually gets done, then reviewed with you before development starts.
04
Development
Engineering runs in short, reviewable increments so progress stays visible and changes stay cheap.
05
QA
Functional and integration testing, plus performance and security checks, run against every release candidate.
06
Deployment
Releases go out through a controlled process, with environments, rollback, and monitoring in place.
07
Support
After launch we maintain, monitor, and extend the application as the business changes.
- Clear business and technical requirements
- Scalable and maintainable architecture
- Security and data protection
- Quality assurance and testing
- Performance optimization
- Documentation and knowledge transfer
- Reliable post-deployment support
Industries we serve
Sectors where this work comes up most often.
- Financial Services & FinTech
- Professional Services
- Logistics & Transportation
- Real Estate
- SMEs and Corporate Enterprises
Ready to scope this out?
Send over what you have — a brief, a spec, or just the problem — and we will come back with an approach.