What Happens When Engineers Take Over Sales (Hint: Automation Happens)

At Kodable, we’ve always believed that engineers should spend time building — not filling out spreadsheets or writing proposals.

But as our workload grew, we faced a familiar problem: every new lead required a detailed cost estimate, project plan, and team structure. Doing this manually for each inquiry could take days — sometimes a full week — before a client even got a proposal.

So we asked ourselves: Can we automate this too?

The Challenge: Time-Consuming, Repetitive Work

Every project request followed the same path:

• Review the client’s brief.
• Break it down into features and stages.
• Estimate development time, team composition, and costs.
• Build a roadmap and write a commercial offer.

This was accurate — but painfully slow. Each step required context switching between engineering, management, and sales. For a technical team like ours, it drained focus and momentum.

We wanted a system that could:

• Read a project description.
• Understand the scope.
• Generate a realistic timeline, team plan, and cost breakdown.
• Then package it all into a clear, ready-to-send commercial proposal.

Our Solution: AI-Powered Estimation Engine

We built an internal AI assistant trained on our past projects, processes, and pricing logic.

Here’s how it works today:

1. Input — we upload the client’s request or short project brief.
2. Decomposition — the AI breaks it into components (frontend, backend, design, infrastructure, QA, etc.).
3. Estimation — based on historical data, it suggests development time and cost ranges.
4. Team Planning — it recommends an ideal team size and roles (e.g., 1 frontend, 1 backend, 1 PM, etc.).
5. Timeline & Proposal — finally, it generates a draft of the commercial proposal, complete with milestones, delivery phases, and total budget.

The first version usually looks great at a glance — clean, structured, and professional.

Reality Check: Optimistic, but Getting Smarter

Of course, it’s not perfect (yet).
AI tends to be too optimistic — especially when estimating timelines. Sometimes it forgets about edge cases or underestimates integration complexity.

That’s why every proposal still goes through human review.
But even with corrections, it’s a completely different experience from writing everything manually.

Instead of spending a week per lead, we now spend a few hours refining and validating AI-generated drafts.

We’ve cut proposal preparation time by over 80%, and we can respond to new leads faster than ever.

What’s Next: Smarter Predictions and Continuous Learning

Our next step is to make the system learn from its mistakes — and our adjustments.

Each time we correct a project’s estimate or timeline, that data feeds back into the model. Over time, it’ll learn which assumptions are too optimistic and which are spot-on.

We’re also working on connecting the estimator to our internal analytics and time-tracking data.
That will allow the model to ground its predictions in real delivery metrics — not just patterns from proposals.

The goal is simple:
A fully automated system that can take a client brief and generate a realistic, data-driven project plan and proposal within minutes — accurate enough to trust, fast enough to scale.

The Bigger Picture

For us, this isn’t about replacing people — it’s about removing the bottlenecks that slow teams down.
Every repetitive task we automate gives back hours that can be invested into what really matters: strategy, design, innovation, and growth.

And we realized — it’s not just our problem.
Many teams waste valuable time on the same routine work: estimating projects, building proposals, and managing endless spreadsheets.

So we decided to turn our internal solution into something others can use too.
If your company spends days preparing estimates or proposals, we can help you automate that process just like we did — using AI systems that understand your data, your logic, and your workflow.

We’re engineers, not salespeople.
And that’s exactly why we’re good at building tools that make business processes faster, smarter, and more efficient.