Tracker is an ATS, CRM and back office in one system, sold to staffing firms across four plans. Kepler is one edition with an assistant that reads every CV, note, email and call transcript you hold and proposes changes rather than making them. Neither product does the other one’s job, and this page is written on that basis.
Tracker and Kepler answer different halves of a staffing business. Tracker puts the ATS, the CRM and the back office in one system — timesheets, expenses, invoicing, shift planning, candidate compliance and payroll integrations with QuickBooks, Xero and Sage — across four plans, two of which are quote-only. Kepler has no back office at all and does not pretend otherwise; what it has is one assistant that reads every CV, note, email and call transcript in the workspace, matching that shows the evidence behind each requirement, per-field history with undo, and one published price of USD 119 per user per month with every feature switched on.
Last checked 6 Sep 2026 · Written from Tracker's own public documentation and pricing pages. Tell us if we have something wrong and we will correct it.
Kepler is USD 119 per user per month billed annually, with every feature included and unlimited records. Tracker publishes prices for its Launch and Core plans and quotes Professional and Enterprise; its REST API, timesheets, multi-channel sequences and candidate portal all start at Professional.
Kepler’s search runs semantic and keyword retrieval together across candidates, CVs, notes and conversations, so an answer can come from a call transcript rather than a field. Tracker’s candidate search is Boolean and semantic across more than eighty filterable fields and parsed résumés.
Emails, calls and messages become proposed field updates and tasks that a person accepts or rejects, with the source attached. Every field keeps its own history, with the source of any AI-suggested change and an undo.
Dimensions where Kepler is the stronger product. Tracker is ahead of us on back office, timesheets, expenses, invoicing, candidate compliance, two-way SMS, telephony, job multiposting, video interviewing and a mobile app, and the blog post covers every one of those in full.
| Kepler | Tracker | |
|---|---|---|
| The assistant | ||
| What search readsThe corpus, not the ranking. | Candidates, CVs, notes and conversations, semantic and keyword together | Boolean and semantic search across 80+ filterable candidate fields and parsed résumés |
| Scope of the assistantOne panel, or the whole workspace. | App-wide sidebar with roughly fifteen tools and @-mentions of specific records | EVA, a conversational AI grounded in your Tracker data, driven by voice or text commands |
| Acting on an answerReading is half the job. | Creates and updates records and saves a result as a list — behind an approval step | Ranks, summarises, drafts emails and texts, and reformats résumés on command |
| Matching | ||
| Evidence per requirementCan a consultant see the reasoning? | A verdict and the supporting evidence for every criterion, expandable under the row | An AI ranking engine that learns from candidate engagement alongside résumé ranking |
| Where the criteria liveWho decides what counts for this role. | Per-job criteria you write and edit, applied to that job only | A ranking layer over the job spec, past success in similar roles and recruiter feedback |
| Trusting the record | ||
| Field-level historyWhat changed, who changed it, and from what. | Per-cell history with the source of every AI-suggested change, and undo | Not described in Tracker’s published feature pages |
| Two people, one recordThe quiet data-loss bug in most CRMs. | Optimistic concurrency, so a stale edit is refused rather than silently applied | Not described in Tracker’s published feature pages |
| Updates out of conversationsApplied, typed in, or proposed for review? | Emails, calls and messages become proposed field updates and tasks you approve or reject | Outlook and Gmail add-ins summarise the sender and let you create records, notes and tasks by hand |
| Meeting and call notesWho writes them up. | A notetaker joins the call and files the summary, next steps and full transcript on the record | Click-to-call, screen-pop, automatic call logging and call recording through telephony integrations |
| Running the desk | ||
| Automations you can auditKnowing what is running without asking support. | A register of everything that runs by itself — what it reads, what it writes, when it last ran, and a switch | AutoAction, Watchdogs and advanced workflow triggers, from the Professional plan upward |
| Sourcing from a profileWhat the extension tells you before you import. | Whether the person is already in your database and what has changed since last time | Capture parses résumés and profiles from job boards and PDFs, and checks for an existing record first |
| API and webhooksWhether you can build on it. | Public REST API with scoped keys, plus outbound webhooks with delivery logs and redelivery | REST API access from the Professional plan; unlimited API calls on Enterprise |
| Custom reportingWhich plan you need before you can build one. | Billings, delivery and consultant splits read from real placements, on the one edition | Custom reporting from Core; full custom reporting and scheduled reports from Professional |
| Getting in and paying | ||
| EditionsHow many decisions before you can buy. | One edition. Every feature included, unlimited records and storage | Four plans — Launch, Core, Professional and Enterprise |
| Published pricingWhat you can work out without a call. | USD 119 per user per month billed annually, published in full | USD 79 Launch (up to five recruiters) and USD 99 Core, monthly; Professional and Enterprise on quote |
| CommitmentWhat you sign before you have lived in it. | Annual or monthly billing, and volume pricing on request above fifty seats | A six-month minimum commitment; annual discounts exist but are not published |
| MigrationWho does the unglamorous half. | Done for you on every plan — extraction, mapping, de-duplication, fifty of your own records to check first | The team assists with migration; white-glove onboarding is listed on Professional and Enterprise |
Tracker’s candidate search is Boolean and semantic across more than eighty filterable fields and the résumés it has parsed, and EVA answers on top of your Tracker data. Kepler’s assistant sits in a sidebar on every page and searches candidates, CVs, notes and conversations together, so a match can come from something a candidate said on a recorded call rather than from a field somebody remembered to fill in.
Active data engineers in London who have used Kafka in production, available within a month
Found 4 candidates. Three mention Kafka on their CV; one said it on a recorded call last week.
| Candidate | Current employer | Notice | Why it matched |
|---|---|---|---|
| Sophia Bennett | Monarch Analytics | 1 month | Kafka streaming for card transactions at Halcyon CV |
| Amir Hassan | Northwind Capital | 2 weeks | Kafka feed for the risk platform CV |
| James Okafor | Juniper Systems | 3 months | Rebuilt the Kafka clickstream pipeline CV |
| Oliver Chen | Northwind Capital | Immediate | Mentioned running Kafka on the 2 Sep call Call note · 2 Sep |
Both products rank a pool against a role. Tracker’s AI ranking engine learns from ongoing candidate engagement and applies that alongside résumé ranking. Kepler writes the criteria for the job itself, then gives every requirement a verdict and the text from the candidate’s own record that supports it — so a consultant arguing with a shortlist has something to argue with.
| Candidate | Match | Role title | Current employer | Skills | |
|---|---|---|---|---|---|
| Sophia Bennett | 92Strong | Senior Data Engineer | Monarch Analytics | Python, Spark, AWS, Terraform, dbt | |
| Amir Hassan | 81Good | Data Engineer | Northwind Capital | Python, Spark, EMR, SQL, Airflow | |
| James Okafor | 74Good | Senior Data Engineer | Juniper Systems | Spark, Azure, Databricks, Kafka, Scala | |
| Mei Tan | 68Weak | Engineering Manager, Data | Atlas Cloud | AWS, Leadership, Python, Snowflake | |
| Elena Rossi | 55Weak | Analytics Engineer | Forma | dbt, SQL, Python, Looker | |
| Oliver Chen | 49Off spec | Platform Engineer | Northwind Capital | AWS, Kubernetes, Terraform, Go |
Assessment
A strong fit for the brief. Sophia has run a production Spark platform on AWS and has managed a team through a migration. Financial services exposure is via a payments client rather than a bank.
Criteria · 3 of 4
Decision
↑ ↓ next candidate · Esc close
Tracker’s Outlook and Gmail add-ins put a summary of the sender in the sidebar and let you create the record, the note or the task from there yourself. Kepler reads the thread, the call and the message and comes back with the change already written — a proposed field update or task, with the source attached, that you accept or reject.
Three candidates · this week
Re: Senior Data Engineer at Northwind
Thanks for sending the details over. The role sounds great, and I can start on 3 October if the timing works for them.
Are you still keeping half an eye out?
I handed my notice in this morning, so I am actively looking now.
James · 11:26For my next move I am looking for £105,000. I would want a step up for a move.
| Candidate | Available from | Status | Expected salary | Notice period | Company | Owner | Skills | |
|---|---|---|---|---|---|---|---|---|
| Sophia Bennett | Not set | Passive | £90,000 | 1 month | Monarch Analytics | Priya Nair | ||
| Amir Hassan | 14 Oct 2026 | Passive | £85,000 | 2 weeks | Northwind Capital | Priya Nair | ||
| James Okafor | Immediate | New | £100,000 | 3 months | Juniper Systems | Tom Reilly | ||
| Mei Tan | Not set | Passive | S$160,000 | 2 months | Atlas Cloud | Tom Reilly | ||
| Elena Rossi | Not set | Active | €78,000 | 1 month | Forma | Tom Reilly | ||
| Oliver Chen | Immediate | New | £88,000 | None | Northwind Capital | Priya Nair | ||
| Rahul Menon | 2 Nov 2026 | Active | £92,000 | 1 month | Juniper Systems | Priya Nair | ||
| Yuki Tanaka | Not set | Passive | ¥14,000,000 | 3 months | Atlas Cloud | Tom Reilly | ||
| Hafiz Rahman | 20 Oct 2026 | Active | S$145,000 | 2 weeks | Meridian Partners | Priya Nair | ||
| Clara Nowak | Not set | New | €84,000 | 1 month | Forma | Tom Reilly | ||
| Daniel Okonkwo | Immediate | Active | £78,000 | None | Northwind Capital | Priya Nair | ||
| Ana Ferreira | 8 Dec 2026 | Passive | €96,000 | 3 months | Juniper Systems | Tom Reilly | ||
| Tomas Novak | Not set | Active | €71,000 | 1 month | Monarch Analytics | Priya Nair | ||
| Grace Adeyemi | 27 Oct 2026 | Active | £105,000 | 2 weeks | Atlas Cloud | Tom Reilly | ||
| Ivan Petrov | Not set | Passive | €88,000 | 2 months | Forma | Priya Nair | ||
| Leila Haddad | Immediate | New | £82,000 | None | Meridian Partners | Tom Reilly | ||
| Marcus Reid | 16 Nov 2026 | Active | £98,000 | 1 month | Monarch Analytics | Priya Nair | ||
| Nadia Kaur | Not set | Passive | S$172,000 | 3 months | Northwind Capital | Tom Reilly |
Kepler's CV parsing and formatting are ported from RemakeCV, our own product, which 300+ recruitment agencies use. The migration that fills your database on day one runs on an engine that has been reading real agency CVs for years, not on something written for this launch.
RemakeCV is a Kepler product. It is the same team and the same code, which is why we are willing to point at it — and it is the only outside evidence on this page, because Kepler itself is new and has no customer stories yet.
Whatever your current system gives you, plus any loose CVs and spreadsheets sitting in folders. If you are not sure how to get the export out, we will walk you through it.
Extraction, mapping, de-duplication and validation — the unglamorous half most vendors leave on your desk. Your custom fields are recreated rather than flattened into notes.
Fifty of your own records, fully parsed — your people, not a demo set. Tell us what we got wrong and we fix it and re-run, as many times as it takes.
The full database goes in, mailboxes and calendars connect, and history backfills onto the right records. We stay on it until your team is working in Kepler.
£89 per user / month, billed annually
USD 79 and USD 99 per user / month; two plans on quote
Tracker publishes two of its four plans. Launch is USD 79 per user per month billed monthly, capped at five recruiters, available in USD and GBP only, and sold through LogicMelon rather than Tracker directly. Core is USD 99 per user per month billed monthly. Professional and Enterprise are contact-sales with custom pricing, and Tracker’s pricing FAQ states that a six-month minimum commitment is required and that annual discounts are available on request rather than published.
Which plan you need is the part worth doing before you compare the numbers. Timesheets, payroll integrations, multi-channel sequences, the candidate portal, AutoAction and Watchdogs, and REST API access all begin at Professional; full back office and payroll, shift management and compliance automation begin at Enterprise. Kepler has one edition at USD 119 per user per month billed annually with every feature in it — and, to be clear, no timesheets, invoicing or payroll in it at any price.
It depends on whether you run temporary or permanent desks. Tracker is an ATS, CRM and back office in one system: timesheets, expenses, invoicing, shift planning, candidate compliance and payroll integrations with QuickBooks, Xero and Sage. Kepler has none of that and no plans to gate it behind a tier, because it does not exist. Kepler is the stronger product on the database itself — an assistant that reads CVs, notes, emails and call transcripts, matching with readable evidence per requirement, per-field history with undo, and one price with every feature included. A temp or contract agency should shortlist Tracker. A permanent or retained agency whose bottleneck is finding people in its own data should shortlist Kepler.
As of 6 September 2026 Tracker publishes two prices on its plans page: Launch at USD 79 per user per month billed monthly, capped at five recruiters and available in USD and GBP only, and Core at USD 99 per user per month billed monthly. Professional and Enterprise are contact-sales with custom pricing, and Tracker states a six-month minimum commitment and that annual discounts are available on request rather than published. Kepler is USD 119 per user per month billed annually, which is USD 1,428 per seat per year, with one edition, every feature included, unlimited records and free migration. Additional AI capacity is available on request.
Yes. Tracker describes TrackerAI as three layers — generative AI that scores candidates against a job spec, agents that handle background tasks, and EVA, a conversational AI grounded in your Tracker data. EVA takes voice and text commands to rank candidates, summarise profiles, write and optimise job descriptions, generate screening questions, draft emails and texts, prepare interview briefings and reformat a résumé onto your template. Kepler’s assistant differs in what it reads and what happens next: it searches candidates, CVs, notes and conversations together, returns results as record sets you can save as a list, and puts an approval step in front of anything it writes.
No. Kepler has no timesheets, no expenses, no invoicing, no payroll and no back office of any kind, and this is a genuine gap against Tracker rather than a roadmap item we are being coy about. The integration story is the honest answer: Kepler ships a public REST API with scoped keys and outbound webhooks with delivery logs and redelivery, included in the single edition, so placements can be pushed into whatever pay-and-bill or accounting system you already run. If you want timesheets and payroll inside the ATS itself, Tracker does that and Kepler does not.
Search that reads notes and conversations as well as CVs and structured fields; an assistant that returns record sets you can save and act on, with an approval step before anything is written; matching that shows a verdict and the supporting evidence for every requirement; a notetaker that joins a call and files the summary, the next steps and the full transcript against the right record; per-field history with undo and the source of every AI-suggested change; optimistic concurrency so two consultants editing one record cannot silently overwrite each other; an automations register that shows what runs by itself, what it reads and writes, when it last ran and a switch to stop it; and a public API with webhooks in the one edition rather than from a quote-only plan.
Kepler runs the migration for you on every plan, at no cost, however large or messy the export. You send an export from Tracker plus any loose CVs, spreadsheets and shared-inbox archives that never made it into the system; Kepler handles extraction, mapping, de-duplication and validation, and rebuilds your custom fields as real fields rather than flattening them into notes. Before the full load you review fifty of your own records fully parsed, and anything wrong is corrected and re-run. Activity, stages and history come across, not only names and email addresses, and a full workspace export is available at any time with no exit fee.
Bring your hardest search to a 15-minute call. We will run it live, on real records, and talk through what a migration would look like.