Jobwise
Collaboration
We build systems, not just software.
TGonix is an AI systems and software studio. We start by auditing how a process actually runs today, then build the agents, automations and internal tools that remove the manual steps, with the logging, access control and documentation needed to operate them afterwards.
- AI agents & RAG
- Workflow automation
- Internal tools & cloud
Temuri Nanava
Founder & CEO
15+ years in IT infrastructure, automation, operations and technical delivery.
Focused on AI systems, RAG, agents, internal tools and practical business automation.
Three-time founder, behind TGonix, Jobwise and Opero.
How we work
01Discover
We start with the bottleneck
Every engagement begins with a structured discovery session. We map your current workflow, identify the most painful friction points, and define what a successful outcome looks like in measurable terms.
02Design
Architecture before code
We design the full solution. Agent logic, data flows, integration points and edge cases are resolved before writing a single line of code, which prevents costly pivots later.
03Build
Guardrails before launch, not after
We build with production in mind: clean code, guardrails, error handling and observability are part of the build from the start, not added just before launch.
04Integrate
Wired into your existing stack
We connect the system to the tools you already use, including CRMs, ERPs, Slack, APIs and internal platforms, testing each connection point with care.
05Deploy & scale
Go live, then grow
We do not disappear at launch. We watch real performance, tune behaviour from actual usage, and help you repeat the pattern on the next workflow when you are ready.
Core principles
Execution first
We do not spend weeks planning the plan. We scope fast, design well, and build. Real systems beat perfect decks.
Operable after handover
Guardrails, logging and documentation are part of the build, not a later phase. Your team should be able to run and change the system without us.
Built around real workflows
We study how your business actually works, not how you wish it worked. Systems that do not fit reality do not get used.
Practical over hype
AI should solve your specific problem, not show off the latest model. We recommend what works, not what is trending.