Customize AI adoption to your real workflows
An LLM or AI tool that performs well in a demo doesn't always perform well on your claims, your workflows, or your edge cases. Swept builds solutions from the other direction: starting with what your team actually does, identifying where AI produces real value, and building only that.
A common version of current AI adoption that seems like a good idea in theory but can break the bank in reality is when AI usage is indiscriminately encouraged and broadly accessible. It's easy to simply assume some degree of ROI, especially in the race to demonstrate relevance through quick AI implementation. Not every task needs AI, just as not every workflow benefits from using the most expensive LLM. Identifying the difference (with proof) is the work of optimizing.
This is where Swept comes in. We don't use a template or industry-agnostic architecture. Instead, we gather evidence and create a workflow-based build that follows that proof, and we do it with the recognition that time is of the essence.
What We Do
Baseline before build (workflow-centric)
A dedicated Swept engineer works with your team to assess AI literacy across departments, identify priority use cases, and define the integration surface: internal systems, file repositories, APIs, and data sources. The output you receive is a scoped project grounded in what your team actually does today. What gets built, and where, reflects your workplace and your workflows.
Identify AI's place
Not every task produces value when paired with AI. Some do, clearly and measurably, while others look promising until you run them against real data. Swept's evaluation process tests candidate workflows under real conditions before a solution is built, so that your investment follows evidence, not vibes.
Build on your architecture, at your pace
No two organizations work the same way. We build the integration layer: connectors to your core platforms, data classification rules, and authentication that is enforced at every connection point. In other words, we don't replace your existing systems; we extend them. Department-by-department rollout means your organization isn't asked to change everything at once. Our builds are designed to support every downstream project that follows; getting it right once will compound your results over time.
Supervision and monitoring to maintain optimization after deployment
Usage patterns in action reveal things that scoping can't. When employees find their own ways to use AI tools (such as summarizing documents, routing requests, and extracting data), those patterns become signals. Swept monitors what's actually happening in production and identifies where a general-purpose tool is doing specialized work that would perform better, and cost less, than a purpose-built agent, as well as the reverse.
Track everything to address your governance and compliance needs, keeping you audit-ready
Every workflow integration, configuration change, and agent deployment is logged. The record exists from day one and feeds into your governance reporting, so your AI implementation is continually up-to-date and audit-ready.
Remain LLM-agnostic
Our workflow solutions are compatible with any LLM or combination of models. Your existing vendor relationships are integrated into a unified environment. When we identify that a particular task may be optimized using a different model than the one currently in use, the switch is straightforward because your workflows aren't tied to a single vendor's ecosystem.
Continual support: before, during, and after deployment
Swept engineers embed with your team through onsite kickoffs, midpoint reviews, and final handoffs. Paired working sessions build your team's capability as each project ships. Our goal for you is not dependency, but instead to provide a successful transfer (and further support only if warranted and desirable).
What You Get
- A named engineer accountable to your project scope: no support queues
- Use-case identification that is grounded in your actual workflows
- An evaluation of the proper AI tools for your needs, giving you evidence before investment
- A sense of urgency to match your own
- Integration with your existing systems via your architecture, at your pace
- Department-by-department rollout with extensive training and ongoing support
- Production monitoring to continually identify optimization opportunities
- LLM-agnostic implementation: the right model for each workflow