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Proposal generation, engagement reporting and utilisation intelligence.

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Industry overview

Inside a professional services operation

The most expensive people in the firm spend a meaningful share of the week on work no client pays for: assembling proposals from previous proposals, writing status reports, and reconciling time. Utilisation is measured monthly and understood too late to act on.

The economics of a professional services firm are simple and unforgiving: revenue is people multiplied by rate multiplied by utilisation. Two of those are hard to move. The third leaks continuously through work that has to happen and cannot be billed, and it leaks worst at the senior end where the rate is highest.

Proposals are the clearest case. A partner assembles a proposal from previous proposals, which means finding them, remembering which one was closest, and rewriting it for the current situation. The knowledge required to do this well is exactly the knowledge that makes them expensive, and the mechanical part of the task, finding, assembling, formatting, checking consistency, is most of the elapsed time.

Status reporting is the recurring version of the same problem. Every engagement produces a report, most of the content is derivable from what has actually happened in the delivery systems, and it gets written by hand anyway because assembling it from the systems takes longer than writing it from memory.

Time capture is the quiet one. Timesheets completed on Friday from memory are systematically inaccurate in a predictable direction: work that was clearly billable gets recorded, and the fragments do not. Those fragments are a real share of the week, and the firm never sees them because nothing recorded them.

Utilisation is measured monthly, which means the month is over before anyone can act. A person who was underutilised in the first fortnight could have been redeployed if anyone had known, and by the time the report arrives that fortnight is a fact rather than a decision.

Underlying all of it is a knowledge problem: the firm has done this work before, and the constraint on reusing it is confidentiality rather than search. Which makes the boundary design the actual engagement.

Common challenges

Challenges we see across professional services

If three or more are true, the rest of this page is about your operation.

  • Partners assemble proposals by finding a previous one
  • Status reports are written from memory rather than from the delivery record
  • Timesheets are completed on Friday for the week
  • Utilisation is understood after the month it describes
  • The same question gets researched twice because nobody could find the first answer
  • Nobody can say what a proposal actually costs the firm to produce

How we help

Five practices, applied to professional services

AI, cloud, cybersecurity, hardware and programme delivery, one integrated bench, each practice applied to how professional services actually operates.

  1. 01

    AI & Automation

    Agents against the two numbers a firm lives on, utilisation and realisation: intake and conflicts checks, engagement-letter assembly, time-entry narrative cleanup before the bill goes out, and status reporting drawn from Kantata and Jira instead of from a partner’s Friday afternoon.

  2. 02

    Cloud & Infrastructure

    A working environment built for client confidentiality: matter-centric access on Microsoft 365, ethical walls that are enforced rather than remembered, and document infrastructure that keeps privileged material inside the engagement team.

  3. 03

    Cybersecurity

    Security your clients will audit: the questionnaire answers backed by real controls, access reviews, device encryption, logging, plus phishing resilience for the inbox-driven fraud that targets firms holding client funds.

  4. 04

    Hardware & Lifecycle

    A professional fleet that never becomes the excuse: laptops imaged and shipped to the new hire’s desk before day one, loaners staged for the courtroom or the client site, and every retired device wiped to a documented standard.

  5. 05

    Program & Project Management

    The firm’s own change delivered like client work: practice-management migrations, office moves and system rollouts run to a plan, with partner time protected and billable disruption measured before it is approved.

Where we start

Automation candidates

Deliberately mundane. The impressive-sounding workflow is rarely the one worth doing first.

  • Proposals: assembly from prior work, tailored rather than templated
  • Engagement reporting drafted from the actual delivery record
  • Time capture prompted from calendar and system activity
  • Knowledge retrieval across previous engagements
  • Utilisation and pipeline surfaced weekly rather than monthly

Systems we integrate with here

If you run one of these, this is the conversation.

  • Salesforce
  • Microsoft 365
  • Jira
  • Kantata
  • Workday

Our solutions

How we transform professional services operations

What happens today, what changes, and what to watch for as each workflow is automated.

Proposals

Today
A partner finds the closest previous proposal, adapts it, and checks it for the references to the last client that survived the copy.
After
Assembly from prior work against the current requirement, with the consistency pass automatic, so the partner spends their time on the argument rather than on the assembly.
What to watch
Client confidentiality governs what may be reused. The boundary, what may be drawn on, at what level of abstraction, from which engagements, is a policy decision made before anything is built, not a setting adjusted after.

Engagement reporting

Today
Written by hand each period because assembling it from the delivery systems takes longer than writing it from memory.
After
Drafted from what actually happened in the delivery record, work completed, decisions taken, risks changed, for the engagement lead to correct and add judgement to.
What to watch
The draft must be visibly a draft. A report that reads as finished is one that goes out without the judgement that was the point of having a lead write it.

Time capture

Today
Completed on Friday from memory. Systematically under-records the fragments, which are a real share of the week.
After
Prompted from calendar and system activity, so the person confirms and adjusts rather than reconstructing five days.
What to watch
This has to feel like assistance and not surveillance, or it will be resented into uselessness. It is worth being explicit with staff about what is observed and what is not, before it is turned on.

Knowledge retrieval

Today
The firm has answered this before and nobody can find it, so it gets researched again at full cost.
After
Retrieval across previous engagements within the confidentiality boundary, with the source engagement identified so the person can judge relevance.
What to watch
This is the workflow with the most upside and the most risk. Getting the boundary wrong here is a client-confidentiality incident, not a quality problem, so it is scoped conservatively and widened deliberately.

Utilisation and pipeline

Today
Reported monthly, after the period it describes, when nothing can be done about it.
After
Surfaced weekly with the people and the weeks that are at risk named, early enough for redeployment to be a decision rather than a post-mortem.
What to watch
Weekly utilisation data used punitively will change behaviour in the wrong direction, people will fill their time rather than raise a gap. How it is used is a management decision that determines whether it works.

The operating picture

Where the agent layer sits in the engagement lifecycle

Your operating loop todayThe agent layer we deploy into it
01

Pursue

Proposals and pitches assembled overnight from scattered credentials.

Agent layer

Drafts the proposal skeleton from your approved credentials library, matched to the RFP’s actual questions.

02

Engage

Conflicts, engagement letters and matter setup delay the start.

Agent layer

Runs the conflicts sweep, assembles the engagement letter from approved clauses, and opens the matter across systems.

03

Deliver

Status, budgets-to-actuals and staffing live in five systems.

Agent layer

Produces the weekly engagement report from Kantata and the time system, hours, budget burn, milestones, automatically.

04

Bill

Write-offs happen in the gap between work done and bill sent.

Agent layer

Cleans narratives against billing guidelines and stages the draft bill days after month-end, not weeks.

Pursue, engage, deliver, bill, the loop behind every matter. Agents carry the administrative weight at each stage so fee-earners spend the hours the client actually values.

Platforms and systems

Technology we work with in professional services

The systems of record this sector runs on, and why each one matters to a deployment.

Salesforce
Pipeline and client relationships. Where forward visibility on demand comes from.
Microsoft 365
Where the actual work product lives, which makes it both the knowledge source and the confidentiality boundary problem.
Jira
Delivery record on technical engagements. The raw material for a status report that nobody currently assembles.
Kantata
Professional services automation, resourcing, time and margin. Where utilisation is calculated.
Workday
People data. Skills and availability, which is what makes a redeployment suggestion useful rather than generic.

The constraint

What makes this sector harder

Client confidentiality cuts across knowledge retrieval: the value is in previous engagements and the constraint is that most of it cannot be reused freely. Getting the boundary right is the whole design, and it is a policy conversation before it is a technical one.

The confidentiality boundary is the engagement. Everything valuable here depends on drawing on previous work, and most previous work is subject to obligations that vary per client, per engagement and sometimes per document. There is no technical answer to this that precedes the policy answer, and any supplier who starts building before the policy conversation has happened is creating a liability.

The boundary is also not uniform. Some clients permit reuse at the level of approach and method; some permit nothing beyond the fact of the engagement; some have specific carve-outs. A single global setting cannot express that, so the design has to carry per-engagement rules and default to the most restrictive when the position is unclear.

Partner adoption is the other constraint and it is a real one. Partners are busy, sceptical, and have working methods that produce results. A tool that requires them to change how they work will be used by the people who have time, which is not the people whose time is most valuable. So the design has to meet them inside the tools they already use.

And there is a cultural trap worth naming: measuring utilisation weekly can be used to help or to police, and the two produce opposite results. Used to spot a gap and redeploy, it is valuable. Used to interrogate individuals about their week, it teaches people to look busy, which destroys the signal and some goodwill with it.

Hands, charts and a tablet over a working table mid-engagement.

Compliance

Compliance that shapes professional services deployments

The regimes your organisation operates under, and what each one constrains in a deployment. We design to these from the first architecture diagram, they describe your obligations rather than our credentials, and VSI's own position publishes only once it is substantiated.

Client confidentiality obligations
Vary per client and per engagement. The design carries per-engagement rules and defaults to the most restrictive when unclear.
Conflicts of interest
Knowledge retrieval must respect conflict walls. Retrieval crossing a wall is a serious incident, not a permissions bug.
Professional privilege, where applicable
Some engagement material carries privilege that automated processing could jeopardise. It is excluded rather than protected by configuration.
Employee monitoring expectations
Time capture from activity has to be transparent to staff about what is observed, before it is turned on.

How we work with public-sector and regulated buyers

Success stories

Results in professional services

Engagements in this sector, with the figures drawn from project records under a named attestation, and the method behind every number on its own page.

Project Management Maturity Practices Yield Improved Operational Efficiencies

Multi-billion dollar consulting firm

40%

Three years

Fast-Track PMO Implementation Rescues Troubled Projects and Improves Customer Satisfaction

Largest privately-held staffing company in United States

100% recovered

12+ months

All case studies, filterable by sector

The first month

What starting looks like

What actually happens, week by week. Note where the design conversations sit, before the build, not after it.

  1. 01Week 1

    The confidentiality boundary, with whoever owns risk in the firm

    The confidentiality boundary, with whoever owns risk in the firm. What may be drawn on, from which engagements, at what level of abstraction. Nothing gets built before this is written down.

  2. 02Week 2

    Time study on where non-billable hours actually go, from the firm’s own data rather than from an estimate

    Time study on where non-billable hours actually go, from the firm’s own data rather than from an estimate. This usually reorders the priorities.

  3. 03Weeks 3-4

    One workflow with a small group of willing partners, usually proposal assembly, because the value is immediate and the confidentiality position is easiest to control

    One workflow with a small group of willing partners, usually proposal assembly, because the value is immediate and the confidentiality position is easiest to control.

  4. 04End of month

    Measured against the week-two study, with a decision on whether to widen and which workflow is next

    Measured against the week-two study, with a decision on whether to widen and which workflow is next.

Next step

A free 20-minute professional services assessment

Proposal generation, engagement reporting and utilisation intelligence.

No preparation required and nothing to install. Bring the workflow that costs you the most hours; leave with a view of what we would automate first, what it depends on, and what we would not touch.

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Questions

Asked often enough to answer here

How do you stop one client’s material reaching another engagement?
Per-engagement rules rather than a global setting, defaulting to the most restrictive position when the status is unclear, and conflict walls enforced at retrieval rather than by convention. The boundary is written down in week one with whoever owns risk in the firm, before anything is built. This is the one area where we would rather deliver less capability than take a position we cannot defend.
Will partners actually use it?
Only if it works inside the tools they already use and requires no change to how they work. That is a design constraint we take seriously because the alternative is a tool adopted by the people with spare time, who are not the people whose time is most valuable. We start with a small group of willing partners for the same reason, voluntary adoption that spreads beats a mandate that gets worked around.
Is the time capture surveillance?
It should not feel like it, and whether it does is mostly about transparency rather than technology. Staff should be told what is observed and what is not before it is switched on. The purpose is to stop the firm losing the fragments that never make it onto a Friday timesheet, that is a firm-level revenue question, not an individual performance one, and framing it otherwise makes it fail.
What does the proposal workflow actually produce?
A draft assembled from relevant prior work within the confidentiality boundary, with the consistency checking done, dates, defined terms, references to the previous client that survived a copy. What it does not produce is the argument, which is the part clients are buying and the part a partner should be spending their time on.
Do we need to change our practice management system?
No. Integration is against what you run. Where a system’s data is too poor to support a workflow we will say so plainly, for example, utilisation intelligence needs time data of a certain quality, and if the time data is unreliable then fixing that comes first because everything downstream inherits it.
How do you measure whether this worked?
Against the week-two time study, which measures where non-billable hours actually go in your firm before anything changes. That baseline is the thing that makes the result arguable rather than asserted, and it is worth having even if you go no further, most firms have never measured it and are surprised by where the hours are.

Usually bought with

The delivery underneath

Other sectors

We also deploy in