Cody Solutions makes the handoffs work

At an international cosmetics distributor, the obstacle to selling beauty products was an ugly little journey. A salesperson assembled an offer from spreadsheets, product catalogues and email. Somebody checked the price. Somebody else approved it. Days passed. Cody Solutions’ account of the project describes a business losing ground while its offers made the rounds. The first thing breaking down was coordination.

A sales quote with too many stops

The distributor, unnamed under a confidentiality agreement, had roughly $50 million in annual revenue. Pricing inconsistencies were damaging trust, and managers lacked visibility into approvals. Cody built an offer-generation engine using OpenAI, connected product and pricing information from SAP, and hosted the infrastructure on AWS. It added role-based routing, notifications and status tracking. A validation layer checked for missing fields, inconsistent prices and policy violations before submission.

Cody reports 52% faster approvals and 43% fewer offer errors. Preparation moved from days to hours. Those are vendor-reported results from one engagement. What makes the example useful is its anatomy: the work crossed several systems, and the solution followed it across them. A faster draft alone would have left the approval queue untouched.

The investigation comes first

This is the territory Cody occupies: custom engineering for businesses whose information and decisions travel badly. Its services include business process automation, software development, AI implementation, interface design, audits and staff augmentation. Customers can bring a stalled workflow, an unfinished product or a shortage of engineering capacity. The company sells the expertise to investigate and build around those problems.

Its business-process service describes an audit-led approach, tailored implementation and continuing support. Process mining examines how work actually moves through systems. The attraction is straightforward: a manager’s explanation of a process may leave out the repeated correction, unofficial spreadsheet or waiting period that makes it expensive. Measure that journey before deciding which part deserves software.

The website attaches a condition to discovery: if Cody cannot identify at least $100,000 in savings, the process research is free. That makes the diagnostic commercially interesting. Identifying savings and collecting them remain separate events; implementation, adoption and operating expenses still affect the return.

A product company learns to build for others

Cody’s own history begins with a product business in 2015. Its timeline records a product sale in 2018, followed by outsourced development, then the creation of Cody Solutions in 2019. That sequence explains the move into services without requiring a romantic origin myth. Today Max Gontar is CEO and co-founder; George Gontar is COO. The company describes delivery locations spanning the United States, Poland and Ukraine.

The public offering is broader than a single automation tool. Cody markets to enterprises and smaller businesses across finance, logistics, healthcare, retail and education. Its service pages name customers including Stobox and Moeco. The useful distinction is the delivery model: customers hire a team to adapt software to a particular operation. They must also compare that choice with hiring internally or using another implementation consultancy.

Sometimes the answer is a data warehouse

For Arab Bank Switzerland, the published problem was fragmented crypto market information, news feeds and real-time updates. Cody describes building an AWS and Databricks warehouse, automated pipelines and a data layer ready for machine learning. Before sophisticated customer analysis could be useful, the information had to become consistent and available. The case gives an approximate 19-month return-on-investment period - a useful counterweight to expectations of instant payback.

Public-sector work presents another version of the same difficulty. For an energy-efficiency agency, Cody built a central information registry with public listings, connections to state platforms and different access rights for officials, providers and citizens. Delivery used two-week sprints with testing and operational support. Here the valuable feature was a dependable shared record that different people could use under different permissions.

The bill includes the unglamorous work

Cody’s Clutch listing advertises $50-$99 hourly rates and a $50,000 minimum project size. Separate workshop packages run from $10,000 to $50,000. These figures describe advertised offers, rather than the budgets of the cases above. A buyer needs a scope covering integration, testing and support before those numbers become a decision.

The company’s framework also includes onboarding and post-launch care. That matters because a technically successful deployment can leave the old routine alive beside it. Training takes staff time. Monitoring takes attention. Maintenance continues after the celebratory demonstration. Comparing suppliers on the build price alone leaves part of the purchase outside the calculation.

“AI should give people back the ability to work on interesting problems”Max Gontar / September 2026

Give the agent a boundary

Cody now also offers agentic process automation: software agents connected to business tools and workflows. Its governance guidance calls for limited permissions, recorded actions, exception routing and human approval for consequential steps. Those details set practical conditions for deployment. Unreliable inputs, unclear ownership or an approval process nobody can explain make a poor foundation for autonomous action.

Its recent work reaches beyond commercial operations. In June 2026, Cody reported engineering delivery for Ukraine’s Obrii labour-market ecosystem. In September it announced UN Global Compact participation. The Obrii employment numbers are programme targets, rather than completed outcomes. That distinction deserves to survive the sales pitch.

There is a modest experiment a reader can copy now. Pick one transaction. Follow it from request to completion. Count the waiting, rekeying and corrections. Assign somebody responsibility for the exceptions. Then ask what removing that friction would actually be worth. The answer may justify a substantial software project. It may also reveal that the first useful change is agreeing who approves the quote.