What we build.
Why we built it.
How we work.

It’s the progression we walk every client through, and it reflects how we think about AI adoption in the real world.

Stage 1 (Understand): Before anything is built or automated, someone has to know your systems deeply. What actually runs your operations, where the bottlenecks are, what your data looks like. This is advisory work, and most companies skip it. That’s usually why their AI initiatives fail.

Stage 2 (Augment): Once we understand the terrain, we embed AI into your existing workflows. Engineers who use AI tooling throughout the dev cycle. Automated QA. Intelligent integrations. The output is faster delivery and fewer errors, but humans are still making the decisions.

Stage 3 (Agentic): At this stage, some operations run autonomously. An AI agent monitors your pipeline, drafts follow-ups, flags anomalies, preps your meetings, and executes recurring tasks, without being asked. Atmobot is our Stage 3 product. It’s not AI assistance; it’s AI execution.

Most companies are trying to jump straight to Stage 3. The ones who get there sustainably go through all three.

Mid-market companies with real operational complexity, typically 20–500 employees, where the business has outgrown spreadsheets and duct-tape integrations but hasn’t yet built the internal engineering team to fix it.

We have deep experience in 3PL and warehousing (TruckMate, EDI/X12, leading WMS platforms), financial services, and enterprise SaaS integrations (NetSuite, SPS Commerce, Azure). That’s not a limitation, it’s an advantage. We don’t re-learn your platform from scratch on your dime.

We also work with funded startups who need a senior technical partner in the build phase, and with larger organizations that need fractional CTO-level leadership without a full-time hire.

The common thread is systems that tie operations together. In practice that looks like:

Integrations: bidirectional syncs between NetSuite ERP and warehouse management systems, EDI/X12 adapters for SPS Commerce and trading partners, Azure-based webhook and event pipelines with retry logic, dead-letter queues, and monitoring.

Custom platforms: internal tooling with real RBAC, dashboards that show actual inventory values and SKU data (not generic BI templates), customer-facing portals built on your data model.

Cloud infrastructure: Azure Functions and App Services, IaC (Bicep/Terraform), controlled deployment pipelines with canary releases and rollback gates, migration from legacy on-prem to cloud with zero data loss.

AI agents: Atmobot deployments, custom intelligence layers on top of your existing data, agentic workflows that execute tasks not just surface information.

Because that’s where we’ve built the deepest domain experience. Third-party logistics operations run on some of the most complex, integration-heavy stacks in enterprise software, TruckMate, SPS Commerce, EDI, NetSuite, custom WMS implementations layered over years of vendor decisions.

We’ve built systems in this space. We know the failure modes. We know what “bidirectional sync” actually requires when you have retry logic, webhook expiry, and order state machines to account for. We’re not learning your domain on your project budget.

That said, the underlying skills (integration architecture, enterprise data pipelines, cloud infrastructure, AI agent deployment) apply across industries. We work outside logistics regularly, especially in financial services and SaaS.

It means our engineers use AI tooling throughout the entire development cycle, not as a gimmick, but as a multiplier on velocity and quality.

Research and architecture work that used to take days now takes hours. Boilerplate generation, test coverage, documentation, and code review have AI assistance built into the workflow by default. Our senior engineers spend their time on the decisions that actually require senior judgment, not the work that can be systematically accelerated.

The result: you get more output per sprint, better test coverage, and faster iteration cycles. We pass that advantage on in scope, speed, and price, not in margin.

Yes. Full stop. Everything built for your project is yours. We assign all IP to you as part of the engagement agreement. We don’t retain licensing rights, we don’t resell your code as a template, and we don’t build on proprietary frameworks that create lock-in.

We use standard, well-documented tech stacks, TypeScript, Node.js, .NET, React, PostgreSQL, Azure, so you can hand the code to an internal team or a different vendor without needing us to translate.

Because existing tools answer questions. We needed something that executes work.

The AI assistant market is full of chat interfaces that respond when you prompt them. That’s useful, but it still requires a human to notice a problem, formulate a question, review the answer, and then act on it. That’s not a 10x, it’s a 1.5x with a nicer UI.

Atmobot is an agent. It runs continuously, maintains memory across every channel and conversation, executes scheduled work, spawns sub-agents for heavy tasks, monitors your email and calendar, tracks your deals, preps your meetings, and surfaces what matters, without being asked. It doesn’t just assist with operations. It runs them.

We built it because we needed it for ourselves first. Atmosoft is a small firm that operates like a much larger one. Atmobot is a significant part of how we do that.

Three things: memory, initiative, and integration.

Memory: ChatGPT starts fresh every session. Atmobot maintains a persistent knowledge base, clients, deals, team context, decisions, history, and retrieves what’s relevant automatically. It knows who you talked to last week and what you agreed to.

Initiative: You don’t prompt Atmobot for your morning briefing. It sends it. You don’t ask it to prep for a meeting. It does it when the calendar event appears. Proactive execution is the core behavior, not a feature.

Integration: Atmobot connects to your actual systems, email, calendar, Slack, Microsoft Teams, CRM, your data sources. It’s not answering questions about your business; it’s operating inside your business.

If your pain is a specific missing system, an integration that doesn’t exist, a platform that needs to be built, that’s a custom build project. Atmobot doesn’t replace software; it augments the humans who use it.

You’re ready for Atmobot when the bottleneck is operational throughput, when the work is getting done but it takes too many people, too many manual steps, or too much leadership attention to keep it moving. If your team is spending time on meeting prep, email triage, follow-up coordination, pipeline tracking, or information retrieval that a well-configured agent could handle autonomously, that’s Atmobot territory.

Most companies end up needing both, in that order: fix the systems first, then deploy the agent to run them.

This is the right question to ask, and we take it seriously.

Atmobot operates with explicit permission boundaries. It can only access the systems you connect and the data you authorize. Outbound actions, sending messages, drafting emails, making external calls, are configurable and can be gated behind human review. Every action is audit-logged.

We built a policy engine that flags anomalous behavior patterns (bulk sends, credential requests, financial actions, attempts to override its own rules). Nightwatch mode restricts operation during off-hours. The architecture is designed around the assumption that the agent will be wrong sometimes, the guardrails are what keep that from being expensive.

For enterprise deployments, we can discuss on-premise or private cloud options, custom compliance configurations, and SLA-backed response time agreements.

A Discovery Sprint is a 2-week, $8,500 engagement that produces a technical architecture document, integration map, risk/dependency assessment, and a fixed-price estimate for the full build.

Do you need one? If you already have a detailed technical spec and a clear scope, no, we can often move straight to a build estimate. But most companies think they know what they need until an experienced architect looks at their stack. The Sprint exists to surface what you don’t know yet before it becomes a mid-project surprise.

It also gives you something valuable even if you don’t hire us: a credible technical assessment you can use to pressure-test another vendor’s quote, get internal buy-in, or secure budget approval.

Senior engineers. US-based, 5+ years minimum experience in their domain. We don’t use a senior engineer to sell and a junior to deliver.

We use AI tooling to extend what senior engineers can produce, faster research, better test coverage, automated documentation, but the architectural decisions, code review, and client communication are always handled by experienced people. We’re not a prompt-and-ship operation.

1. Conversation, 30 minutes. No deck, no demo. We figure out if what you need is something we can deliver well.

2. Discovery Sprint or direct scope, For complex builds: a 2-week sprint producing a fixed-price estimate and architecture document. For well-defined work: a scoping call and written proposal within a week.

3. SOW and kickoff, Signed statement of work with acceptance criteria, milestones, and delivery timeline. No ambiguity about what done means.

4. Build with visibility, Weekly updates, milestone reviews, and a staging environment you can access throughout. You’re not waiting for a big reveal.

5. Delivery and handoff, Deployment, documentation, and 30 days of post-launch support included. We don’t disappear after go-live.

Faster than most. A well-scoped MVP is typically 8–12 weeks. Integration projects with defined endpoints and clear data models can be faster, sometimes 4–6 weeks. Discovery Sprints are 2 weeks, fixed.

The bottleneck is almost never our team. It’s access to your systems, stakeholder availability for decisions, and scope creep. Projects with a clear decision-maker on the client side who can unblock things move significantly faster. We’ll tell you what we need from you upfront.

The most common failure modes we hear about: scoped for junior, delivered by junior. Estimate that bore no relationship to reality. Delivered a product that couldn’t be maintained after handoff. Disappeared after launch.

Our answers to those specifically: We only use senior engineers. Our Discovery Sprint exists because we won’t give you a fixed-price estimate until we understand your system. We build on standard, documented stacks your next engineer can read. And post-launch support is built into every engagement.

We can’t promise we’re perfect. We can tell you that we keep a small roster precisely because we’d rather do a few things well than spread thin. And we’ll tell you honestly in the first conversation if your project isn’t something we can deliver well.

The Discovery Sprint ($8,500) is designed to be a standalone deliverable, you get real value from it regardless of whether you continue with us. That’s the smallest formal engagement.

For advisory work, the Strategic Advisor retainer starts at $2,500/month for 4 hours, useful if you need senior technical judgment on an ongoing basis without a project commitment.

We don’t take hourly consulting calls or one-off code reviews as standalone engagements. The minimum footprint is a Discovery Sprint or a retainer.

Direct access to senior people, a faster decision loop, and a team that has genuine skin in delivering rather than extending the engagement.

Large firms staff projects with layers. You get a partner who sells, an engagement manager who coordinates, mid-level leads, and juniors who do most of the actual work. You pay for all of those layers. With us, the people you talk to in the sales conversation are the people doing the architecture and reviewing the code.

We also move faster because we don’t have procurement processes, internal approval chains, or 90-day onboarding ramps. When something needs to change, it changes in days, not sprints.

Often, yes, especially for the Augmented Development and Advisory services. A lot of our best engagements are with companies that have internal engineers but need senior-level architecture guidance, specialized domain knowledge (EDI, ERP integrations, cloud infrastructure), or additional capacity for a specific build without a full-time hire.

We work well alongside internal teams. We’re not territorial about code ownership, we document what we build so your team can maintain it, and we can structure engagements to transfer knowledge to your engineers rather than create dependency on us.

We’ll tell you. Directly, in the first conversation.

We’re not a fit if you need a large team immediately, if your project requires expertise we genuinely don’t have, or if your budget doesn’t align with the level of work involved. We’d rather say so upfront than take an engagement and underdeliver.

If we can point you to someone better suited, we will. We care more about being the right call for the right client than closing every deal that comes through.