Build AI agents for enterprise workflows
Build agents that retrieve the right procedures and operate across multi-step processes such as order-to-cash or procure-to-pay, with clear checkpoints for human review.
AI agents for real workflows
AI agents built for production workflows.
As an AI agent development company, Techtribe builds agents that use tools, work with company data, and support business workflows. Our AI agent and automation development starts with bounded tasks, clear permissions, and a defined role for human approval.
One Islamabad-based team · direct founder access · code in your repository
Where it fits
What this service covers.
Connect agents to product tools
Give an agent a bounded set of typed actions so it can look up records, prepare changes, or move a SaaS workflow forward under defined permissions.
Automate repetitive operations with review
Use an AI agent to prepare classifications, recommendations, or next steps, then route sensitive or uncertain actions to a person before execution.
Add an agent to an existing SaaS product
Integrate an agent into a user workflow with the right context, progress state, error handling, and a way to recover when a tool or model fails.
Engineering approach
Designed around the product and its constraints.
We choose the implementation after understanding the user flow, existing systems, and operating requirements. The exact stack and boundaries are agreed during scoping.
Agent orchestration and tool contracts
Bound the agent’s role, available tools, typed inputs and outputs, state transitions, retries, and fallback paths so the workflow stays understandable.
Grounding and permissions
Connect agents to approved company data and retrieval systems, with access rules that match the users and actions involved.
Human control and evaluation
Set approval gates for consequential actions, evaluate representative scenarios, and monitor quality, latency, and cost after launch.
Technology
A stack selected for the system.
Production agents combine an application layer, model and tool integrations, retrieval where needed, and the infrastructure to operate them. These examples come from Techtribe’s published FlowGen Labs work; the project scope determines the final stack.
Python, FastAPI
Agent services and APIs for orchestration and workflow execution.
TypeScript, Next.js
Product interfaces for configuring, reviewing, and monitoring agent workflows.
RAG, vector search
Retrieve relevant procedures and documents to ground agent actions in company information.
AWS, Terraform
Cloud infrastructure and repeatable deployment for the agreed operating environment.
Choose the right scope
Start with the smallest scope that fits.
Package fit depends on the workflow, integrations, and production requirements. We confirm the scope, price, and ship date before work starts.
2 weeks
Basic MVP
$2,500fixed
Founders who need something real to show users or investors, fast.
A narrow agent experience with one core user flow and one AI feature, scoped to validate a specific workflow.
- One core user flow, working end to end
- One AI feature: agent, chat over your data, extraction or automation
- Clean, responsive UI on our design system
- Deployed on a live URL you can share
- Source code in your repo from day one
- 30 days of free support
Not included: Production hardening (evals, monitoring, fallbacks), custom brand design, more than one integration. Everything built here carries forward into Production MVP.
4–6 weeks
Production MVP
$7,000fixed
Teams launching an AI-first product, or a serious AI module, that real customers will depend on.
A production AI workflow with integrations, defined tool contracts, evaluation, and monitoring in the agreed scope.
- UX and UI design in your brand, before we write code
- Production architecture: deterministic flow control, typed tool contracts, model routing with fallbacks
- Web app and backend deployed on your cloud, in your repo
- Auth, billing hooks and admin basics
- Up to 3 integrations into your existing systems
- Eval set and regression tests
- Cost, latency and quality monitoring
- Weekly live demo
- 30 days of free support
Rolling · 30 days' notice
Dedicated Team
$8,000per month
Teams that shipped and want to keep building, or companies that need a senior AI pod without hiring one.
Ongoing agent development when the product needs continued workflows, integrations, evaluation, and operational support.
- 2 engineers (1 senior, 1 mid), full-time on your product
- 1 dedicated project manager: your single point of contact
- Founder oversight on architecture and quality
- Daily standup, weekly demo, shared Slack
- 4+ hours overlap with US Eastern, full day with Europe
- Code in your repo, infra in your cloud, nothing to migrate
- Swap or add engineers with 2 weeks' notice
- 30 days of free support if you pause or wrap up
Relevant work
See FlowGen Labs in practice.
Techtribe’s co-founder spent a year as a core engineer on FlowGen Labs agents inside SAP, working across agent loops, tool contracts, RAG, infrastructure, and developer tooling.
How it works
A clear path from scope to shipped software.
01 · Scope the workflow
Define the users, the task, data access, available tools, and which actions require human approval.
02 · Design the architecture
Set the state model, tool contracts, retrieval path, permission boundaries, evaluation plan, and failure handling.
03 · Build and evaluate
Implement the workflow and test representative scenarios, sharing a working demo each week.
04 · Ship and support
Deploy to the agreed environment, hand over the code, and support the shipped scope for 30 days.
FAQ
AI agent development questions.
What is the difference between an AI agent and a chatbot?
A chatbot mainly responds to a conversation. An agent can also select from defined tools and take steps in a workflow. We scope those actions and permissions explicitly so the system has clear boundaries.
Can an AI agent work with our internal data?
Yes, when the data sources and access rules are understood. We can connect a workflow to an agreed retrieval system and design the agent around the information each user is allowed to use.
How do you keep an agent from taking an unapproved action?
We define permitted tools and action boundaries, then add human approval where the workflow requires it. The right controls depend on the impact of each action and the surrounding system.
How do you test an AI agent before launch?
We create representative scenarios and check the agent’s tool selection, outputs, and failure paths against agreed expectations. Production scopes can include ongoing evaluations and monitoring.
What does AI automation development include?
It starts with a defined workflow and the systems an agent may use. We scope the steps to automate, add approval points where needed, and test the expected and failure paths before launch.
Which package fits an AI agent project?
Basic MVP can validate one focused AI workflow, Production MVP suits an integrated product launch with evaluation and monitoring, and Dedicated Team supports ongoing development. We confirm fit against the scope and current package details.
Book a free call
Planning an AI agent for a real workflow?
30-minute free call. Tell us what the agent should do, which tools and data it needs, and where people should stay in control. We’ll scope a practical first release.
- You talk to a founder, not a salesperson.
- You leave with a recommended package and a rough plan.
- Prefer email? howdy@techtribedev.com