Usually that's a shared drive, a Slack thread from March, and FINAL_v7_REAL. We map the job from trigger to outcome, find where it stalls, and redesign it with the people who do it every day.
The answer might be a simpler process, better data, software you already own, or an agent with a clearly defined job. We agree the improvement and who owns it before we touch anything.
We follow one piece of work from start to finish: who does each step, what they need to know, where it waits, and how it moves to the next person. We look for steps nobody remembers adding, handoffs that take days, missing information, and approvals stuck in someone's inbox.
Then, with your team, we decide what to cut, what a system can handle, what a person should check, and what stays fully human. We define how exceptions get handled, where the output lives, and who maintains it after launch.
Understand the work with the people doing it, compare the options, and agree a baseline, owner, and scope. The next step can be building, advice only, or nothing at all.
Test a redesigned workflow or working model with real users and agreed examples. Define system tasks, human review, exceptions, and acceptance criteria.
Deliver in stages, integrate with your tools, and test against the acceptance criteria. Release happens when the agreed tests and approvals pass. Handover includes docs, runbooks, and named owners.
Watch reliability, adoption, and business results after launch, and decide together whether to expand, adjust, or stop.
Week one is mostly listening. We sit with the people who do the work, read the actual data, and find out which spreadsheet is load-bearing. By the end of the first month you have a map of the workflow, a baseline, an agreed definition of better, and a recommendation you can act on, including the option of stopping there.
A sponsor, people who can answer business and technical questions, access to the relevant systems, and review time on the calendar. If something changes on your side, we talk about the impact before we change the plan.
Before we change anything, we set a baseline and agree how we'll compare results. Depending on the work, that might be prep time, factual errors, handoff delays, adoption, or customer outcomes. Agent counts and messages generated don't count as progress.
At each checkpoint your team reviews working output against the scope. After rollout we check whether people use it and whether the numbers moved, accounting for everything else that changed that quarter.
A seller digs through CRM records, usage reports, support tickets, and old call notes, reconciles the contradictions by hand, and hopes nothing important is missing.
The workflow matches the account across approved sources, checks the seller's access, and builds one brief with source links and timestamps. Missing or stale data gets flagged. The seller reviews it, picks the questions, and owns the conversation.
The seller reports anything wrong. An ops owner maintains source mappings, freshness rules, and the brief format. We measure prep time, factual errors, and actual use against the baseline.
A CSM stitches together renewal dates, usage, stakeholder notes, and open tickets. Nobody trusts the health score, so what gets reviewed depends on what someone happens to notice.
A weekly review combines approved signals with an evaluated risk model and shows why each account was flagged. The CSM checks the evidence, decides whether to call or escalate, and logs the action. The workflow never emails customers, offers discounts, or touches the forecast.
Customer success owns the decisions. A data and ops owner watches source freshness and model performance. We measure warning time and flags acted on, against a control group where practical.
Strategy picks the workflows worth changing. The context layer supplies the data they need. Agent delivery builds the system tasks, and evaluation sets the approval and review boundaries. The GTM services apply all of it to specific teams, and ongoing operation keeps it healthy. Each engagement uses only what the work needs.
We can deliver in your environment or in an agreed hosted setup. Before implementation, we document where data is processed, which providers are involved, and who has access. Client data stays inside the engagement it belongs to. Our SOC 2 Type II program is underway. The agreement spells out ownership of deliverables, pre-existing materials, third-party licenses, and ongoing operation.
Before an agent goes live, your risk, security, or compliance reviewers get an approval pack: what the agent does, which data it reads, the actions it may and may not take, evaluation results against an agreed test set, the guardrails in place, when it escalates to a person, and how every action is logged so it can be reproduced. They decide whether it ships.
No mandatory platform. No agent quota. No 90-slide deck. Your data stays yours. If we're the wrong fit, we'll say so and point you to someone better. That stings us a little every time, and we do it anyway.
| Comparison | The big consultancy | The AI-native startup | Ruvu |
|---|---|---|---|
| Who builds it | A delivery team you meet after signing | Strong AI engineers | The people from the first meeting |
| Revenue and GTM depth | One practice among dozens | Horizontal by design | The only engine we work on |
| First working version | After discovery and a steering committee or two | Fast | Early, on your own data |
| What stays behind | Documentation and a change program | A working model | Context layer, evals, approval pack, runbooks, owners |
| Track record | Decades of delivery | Years of AI projects | Years running these systems from the inside |
Fair question. The firm is young and the experience isn't. We've spent our careers running data, AI, and GTM inside Salesforce, HubSpot, Adobe, and Procore, and before that building a data practice at Slalom. Public software companies work with us today. We also start small on purpose, so you can judge us on working software before you commit to more.
That's how we prefer it. We plug in as an extension of your team with clear owners, so nobody wonders who's driving.
Probably not. Most companies already own plenty of software. What's usually missing is the context underneath it.
Yes. Some of our best engagements end with a clear decision and zero code.
Fixed fee, time and materials, or ongoing support, depending on scope. You'll hear a number early in the conversation.
Tell us where it gets stuck and what better would look like. We'll suggest a sensible place to start and who needs to be in the room.