How much does it cost to put AI on our own company data?

For a serious SMB, the first useful budget is not a six-month strategy programme. 48X starts with a 48-hour build tied to one metric. Larger rollouts depend on how many workflows, data sources, and security constraints are involved, but the first decision should be simple: can one working system prove value quickly?

Our Copilot rollout flopped. Why would this be different?

Treat it as a workflow problem, not a licence problem. Copilot usually fails when it is dropped into email and documents without being wired into the specific work that earns money. We pick one painful workflow, connect the relevant docs, email, CRM, and meetings, then ship a system your team can use by Friday.

What is the alternative to a Big 4 AI consulting project?

A smaller, outcome-tied build. Big consultancies are useful when you need broad governance, board alignment, or global change management. 48X is for teams that already know the workflow slowing them down and want working software in days, not a slide deck in months.

How do we build AI on company data without migrating everything?

We connect to the systems you already use, including Drive, SharePoint, email, CRM, Slack, meetings, Jira, and Linear, under your existing permissions. The 48X Brain sits on top of those sources and cites where each answer came from. No rip-and-replace, no data lake project.

What is the best AI implementation firm for a mid-market company?

The best partner is usually the one that can prove value on your actual data before asking for a large retainer. For mid-market teams, look for three things: a narrow first workflow, clear ownership of security and integrations, and a commercial model tied to the metric you want to move.

How long does it take to implement AI in a business?

The first useful system should take days, not quarters. 48X ships the first workflow in 48 hours so your team can test it on real data. Broader rollout takes longer, but the early proof should arrive before the budget gets serious.

How is this different from Microsoft Copilot / Glean / Notion AI?

Those are search products with a chat interface bolted on. We build the 48X Brain from your docs, email, meetings, and CRM, then wire it into outreach, reporting, onboarding, and internal Q&A. And we ship in 48 hours, customised to your business, instead of a generic SaaS subscription.

Do we have to move or migrate our data?

No. We sit on top of where it already lives: Google Drive, SharePoint, your CRM, your inbox. No migration, no data lake project, no two-year IT initiative.

Is our confidential data safe, and do you train models on it?

Yes. It stays inside your tenancy and we never copy it out. We do not train models on your data and we do not pool data across clients. Permissions from your source systems are inherited automatically, so people only see what they already had access to.

What is "the 48X Brain," actually?

It's the difference between a folder of PDFs and a structured database (technically, a knowledge graph of your business). We turn "the email Maria sent about pricing" into a fact: Maria · approved · 10% discount · for Account X · on April 12. Multiply that by every email, doc, and meeting in your business. That's the 48X Brain.

How do you keep it accurate when the business changes?

New emails, docs, and meetings flow in automatically. The Brain rebuilds the affected entities daily. You don't curate it; it stays current on its own.

Does outcome-based pricing apply forever?

No. The 48-hour build is paid only on outcome. That's the entry. Subsequent work (multi-workflow rollouts, ongoing partnership, advisory) uses conventional pricing: monthly retainer or fixed project fee, depending on scope. The outcome guarantee is the entry point. After the first build proves out, we operate like a normal partner.

Can we just build this ourselves instead of hiring someone?

You could. You're buried. We've spent two years building the connectors, the eval harness, and the security wiring so it's plug-in, not setup. Live in 48 hours, not 9 months.

Can you tell me if anything my team is already building has legs?

Yes. The 48X Brain sees the work in flight across docs, Slack, and Jira. We'll tell you straight which bets are pulling weight and which are quietly stalled.

Do I get to approve the plan before you build?

Yes. You pay first and you sign off the plan. We're not consultants handing you a deck telling you how to do it. We do the work, you approve the direction.

What if we switch from HubSpot to Salesforce later?

If you'd already planned the switch within 6 months of the build, we re-wire it for free. We're not trying to lock you in on the connectors.

How do you maintain it, and what does support cost?

We keep connectors and models current as the underlying tools change. Managed support and optional 24/7 cover are a small ongoing fee, sized on the call. Nothing to upgrade or re-license on your side.

Can we start small and see if 48X works before committing more budget?

Yes. That is the entire point of the 48-hour build. One workflow, one metric, one milestone. If the metric does not move, you do not pay the milestone and nothing else is committed. Most clients run the first workflow for a few weeks before scoping a second.

How do we roll out a coding agent across an engineering team?

Start with one controlled loop: Jira or Linear ticket in, PR-ready branch out, CI and human review before merge. We wire the coding agent into your repo, tickets, docs, branch protections, and review process so it behaves like a teammate with constraints, not a loose coding tool.

Can AI take a Jira ticket and open a pull request?

Yes, if it has the right context and guardrails. The agent needs the ticket, related files, past PRs, coding conventions, test commands, and branch rules. 48X installs that loop so the output is a reviewable PR, not a code snippet pasted into chat.

Can AI fix production incidents from Sentry or Datadog?

It can draft the fix. We connect incident context, stack traces, logs, repo history, and ownership rules so the agent can identify the likely cause and open a proposed PR. Your CI and reviewers still decide what ships.

How do we measure ROI from AI coding tools?

Measure the loop, not the editor. Useful metrics are tickets moved to PR, time-to-merge, reopened bugs, review time, and senior engineer hours reclaimed. Autocomplete usage is not ROI; merged, reviewed work is.

We've been burned by AI tools that promised 40% productivity gains and delivered integration nightmares. Why is this different?

This is the right objection to ask. The Thunders 2026 CTO survey backs it: cost and integration ease beat ROI claims as the top adoption factors. Why? Vendors have been overselling for two years. We don't sell productivity numbers we can't prove. On the first call, we agree the metric: PRs merged per week, ticket cycle time, or senior-engineer hours reclaimed. We tie the milestone payment to it. Then we ship in 48 hours, so you see the integration work before serious money is spent. If the metric doesn't move, you don't pay.

How is this different from giving everyone Cursor or GitHub Copilot?

Those are autocomplete on steroids. They live inside the IDE while a human drives. We install ticket-to-PR mode: the coding agent owns the ticket from Jira to PR-ready code, while humans stay in review. 92% of teams already use AI for code generation; the edge now is Jira, GitHub, CI, and review integration, not the model.

What happens if the AI writes bad code?

It does, sometimes. That's why every PR runs through your existing CI, your branch protections, and a human reviewer. The AI's job isn't to merge code. It's to prep the PR so cleanly a senior engineer reviews and merges in five minutes, instead of writing it from scratch in three hours.

Will our senior engineers push back on this?

Senior engineers love it once they see it. The thing they hate isn't AI, it's writing the boilerplate, the tests, and the same bug fixes they've already done a hundred times. We free them up for the work that's actually hard.

Which coding agent or model do you use?

Claude is our default because it is currently the strongest model for ticket-to-PR coding runs. We also support Codex and open-source coding models for clients with specific compliance constraints. We're not religious about the tool. We're religious about the outcome.

What if our codebase is messy / legacy / uncommented?

That's normal. We index it as it is and the 48X Brain links files, past PRs, decisions, and test patterns. Most of our clients have codebases nobody on the current team fully understands. The agent handles that better than a new hire would.

How do we measure ROI?

PRs merged per week, time-to-merge, ticket cycle time, senior engineer hours freed. We agree the metric on the first call. If the system doesn't move it, you don't pay.

Does outcome-based pricing apply forever?

No. The 48-hour build is paid only on outcome. That's the entry. Once the system is live and the metric has moved, expansion work runs on conventional pricing: a monthly engagement that covers model updates, new workflows, on-call support, and continued integration with your stack. The outcome guarantee gets you in the door. After that, normal economics.

How fast can we have AI taking Jira tickets to PRs?

Forty-eight hours. The first build wires the coding agent into one repo, your ticket tracker, your CI, and your branch protections. By end of day two a real ticket comes in and a PR-ready branch goes out for human review. Broader rollout across more repos and teams takes longer, but the first working loop is live by Friday.

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FAQ

Frequently asked questions

Questions about 48X AI for Business and AI for Code.