Moving on from legacy time coding via Clocktimizer

Foundation Scoping, the product most people still call Clocktimizer, showed pricing teams that there was real value sitting inside their time entries. That was the right first step. What has not moved on is the way it reads that data, and the ceiling it puts on insight is now the thing holding firms back.

What it does

Clocktimizer was built to code time entries for the pricing and legal project management team. It runs natural language processing across billing narratives and sorts the work into fixed buckets: phase, task and activity, or PTA. That is better than no structure at all. The technique underneath it, though, is legacy NLP: it matches keywords against a fixed taxonomy, and the limits build up the longer a firm lives with it.

Accuracy

Keyword bucketing struggles with edge cases. A matter described in slightly different language gets coded wrong, and the data you most need to trust is the data that drifts off without anyone noticing. When you later pull a report to support a pricing decision, you cannot fully rely on what it tells you.

Upkeep

The buckets are only as good as the configuration behind them, so every firm tunes its own by hand. That is heavy to set up and hard to maintain. Each time the firm takes on a new type of work, someone has to go back in and adjust the taxonomy.

Limited scope

Once a matter is reduced to phase, task and activity, that is the limit of what you can ask of it. Clocktimizer cannot profile a matter or extract insight from it. It will help you slice a piece of work into its component parts, but it will not help you describe that piece of work. And because the tool cannot identify reference matters, that job goes back to a partner. So a partner has to weigh in, and expensive time goes on something the data should have handled. Or you guess, and risk getting the reference matters wrong.

How Ayora handles it

Ayora does the task and phase coding, then goes further. It builds a profile of the context around each matter: the role your firm played, the structure of the matter, the key elements of scope, and the other details that make one matter comparable to another. You pull whichever properties are relevant for the job in front of you and query the whole history however you need. The question morphs from "show me everything tagged Phase: Due diligence" to "find the deals that look like this one."

Two things follow. First, you stop interrupting partners for directions every time a new prospective matter comes in, because the comparable is already there in the data. Second, you spend far less time finessing the output, because the profile is richer to begin with and you are not hand-correcting mislabelled entries before you can use them.

The wider point is who this serves. Clocktimizer is built for the pricing team. Ayora's enriched layer is useful across the firm: pricing and LPM, knowledge, finance, innovation, and marketing and business development. Knowledge teams need the history to answer questions about what the firm has actually done. Marketing and BD need reference matters to build pitches and win work. Finance and innovation draw on the same profiles for their own questions. One enriched layer feeds all of them, rather than living inside one team's tool.

The interface

Clocktimizer is a dense web app that takes real training to drive, so in practice the insight stays locked behind a handful of specialists. Ayora is AI-native, and the default way you interact with it is an agent. You turn a set of historic matters into a quote, ask it to run analysis across your data, talk a pricing scenario through and watch it model the options, then pull a colleague in. It does the kind of work an analyst would do, and it does the tedious parts far faster. Because it takes no training to use, you can put it in front of a much wider group, partners included, and they can get a straight answer out of the firm's own data.

With Ayora, you own the data

There is one more difference that matters over the long run. With Clocktimizer, the enriched data lives inside Clocktimizer. It is hard to get out, and in practice you do not own the structured asset you have helped build. With Ayora, the enriched data is yours. You can push it into your own business intelligence tools, build on it, and keep it if you ever move on from Ayora.

Recap

Clocktimizer was the right call when the job was simply to start structuring time data. Ayora goes further: better insight, data the whole firm can use, an asset you own, and a tool you can interact with intuitively. We are building the operational context layer.