OpenAI Assistants & Agents Builds

Overview

What we deliver

We build agents on the OpenAI Assistants API and the new Agents stack, with custom tools, retrieval, and the controls your team needs.

We build production agents on OpenAI’s Assistants API and the newer Agents stack. These platforms give us hosted threads, file search, code interpreter, and function calling out of the box. We use them to ship agents quickly without giving up control over behavior or cost. We start by scoping the agent’s job and the tools it needs. We design custom function tools, set up file search with your documents, and add code interpreter where math or data work is required. We tune system instructions, manage thread state, and add retrieval beyond the built-in vector store when it improves accuracy. We instrument the agent for logging, evaluation, and cost tracking. The result is a focused OpenAI agent that fits cleanly into your product or operations, with a path to iterate as the platform evolves.

Fit Check

Built for teams like yours

Who it's for

Product teams building on OpenAI
Operations teams using GPT for daily work
Engineering teams needing fast time to value
Support teams automating tickets and replies
Analysts using code interpreter for data work

Pain points we solve

Prototypes that stall before production
Function calls that break on edge cases
Knowledge bases the agent cannot reliably search
No clear way to measure quality or cost
Hard to keep up with platform changes

What's included

Capabilities

Everything we cover in this engagement.

Assistants API and Agents stack setup
Custom function tool design
File search and vector store configuration
Code interpreter use cases
System instruction and policy tuning
Thread and state management
Evaluation harness and logging
Cost monitoring and optimization

How we work

Our process

A clear, predictable path from kickoff to outcomes.

01

Define

Set the agent's job, scope, and success criteria.

02

Configure

Set up the assistant, tools, and file search.

03

Integrate

Connect the agent to your product or workflow.

04

Evaluate

Test on real cases and tune instructions and tools.

05

Launch

Deploy with logging, cost controls, and a review cadence.

What you get

Deliverables & outcomes

What you get

Configured OpenAI agent in your account
Custom function tool implementations
File search index with your documents
System instructions and policy files
Evaluation reports and dashboards
Developer and operator documentation

Outcomes you can expect

Faster path from idea to production agent
Reliable behavior on real cases
Predictable cost per task
Clear logs and metrics for every run
A maintainable build that follows platform updates

Timeline

3 to 6 weeks

Engagement

Monthly retainer, Project, Sprint

Tools we use

OpenAI Assistants API, OpenAI Agents SDK, Pinecone, Vercel, Supabase

KPIs we track

Task success rate, function call accuracy, retrieval precision, cost per session, response latency

Client stories

What clients say

"

Our SDRs were spending two hours a day copying lead data between Salesforce, Outreach, and a Google Sheet nobody owned. They mapped the whole flow, stitched it together in n8n, and added a dedupe step we did not even know we needed. Got 38 hours a week back across the team. The SDRs were the ones who pushed to expand it further.

Rebecca F.

"

We were drowning in tier-one tickets about password resets and appointment changes. They built a deflection layer on top of our help desk and kept their agents in the loop for anything sensitive. Volume to humans dropped 58 percent in two months and our patient NPS held steady. The hybrid handoff is the part most vendors get wrong. They did not.

P.M.

Proof