AI agent development: Software that plans, acts and checks its own work.
Agents that use real tools inside clear limits — and the research work behind them: reasoning loops, memory, local models and training our own.
Overview
AI agent development at MoboDevelopers
AI agents are software that plan, use tools and act — reading files, calling APIs, browsing, sending messages and checking their own results. MoboDevelopers builds agents that do real work inside clear limits: typed and validated tools, scoped permissions, bounded retry loops, spending caps and a human confirmation step before anything risky.
Our agents plan a goal into tasks, execute them with tools, verify the output and report back. They can remember context per user, per chat or per project, run on a schedule, and use local open-source models when data cannot leave your infrastructure. Integrations use typed tools or MCP servers with the minimum access each task needs.
Alongside client work we do practical research toward more general AI: reasoning and planning loops, agent memory, tool use and training our own language models. Our local agent MoboAgent and the coding agents inside MoboStudio AI are where that research meets production.
Capabilities
What’s included in our AI agent development.
Planning agents
Agents that break a goal into tasks, execute them with tools and report back.
Tool use
Typed, validated tools for files, code, browsers, APIs and messaging.
Self-verification
Agents that test their own output and retry within a bounded number of attempts.
Memory
Short- and long-term memory scoped per user, per chat or per project.
Local & private models
Agents on local models when data can’t leave the building.
Model research
In-house work on training language models from scratch, tokenisers and fine-tuning.
Deliverables
What you get
- Agent architecture
- Tool and permission design
- Evaluation harness
- Human-in-the-loop checkpoints
- Observability
- Research reports
Technology
What we build with
Agents
- Tool calling
- MCP
- Planner / executor loops
- Schedulers
Models
- Claude
- GPT
- Gemini
- Ollama
- PyTorch
Execution
- Containers
- Playwright
- Queues
- Sandboxed runtimes
MoboAgent runs a local model with real tools, memory and schedules — and asks before anything dangerous.
See the productHow we work
From first message to launch.
A simple path with clear decisions at every step — and working software you can click through early.
- 01
Fit review
We read what you sent and come back with questions — not a sales deck.
- 02
Architecture call
We map the system, integration points, risks and the first milestone.
- 03
Scoped proposal
Deliverables, team, cadence and launch path — in writing.
- 04
Build
Working increments you can click through, in a repository you own.
- 05
Launch & evolve
Deployed behind health checks, documented, and handed over — or run with us.
FAQ
Questions, answered.
Are agents safe to run in production?
With the right design, yes: scoped permissions, validated inputs, bounded loops, spending caps and a human checkpoint for risky actions.
What does your AGI research involve?
Practical R&D: reasoning and planning loops, agent memory, tool use and training our own models — work that makes today’s agents more capable and more reliable.
Can agents use our internal systems?
Yes, through typed tools or MCP servers with the minimum access each task needs.
What can an AI agent actually do for a business?
Common uses are answering customer messages from your own knowledge base, running scheduled reports and checks, triaging tickets, and operating internal tools — always within permissions you define.
Do you build AGI?
No one ships general intelligence today. We research the building blocks — reasoning, planning, memory and tool use — and put what works into agents that do real, bounded tasks.
More ways we build
Let’s build something people haven’t seen yet.
Have a product, platform or ambitious idea? Let’s turn it into working technology.
or write to hello@mobodevelopers.com