Kantiv alternatives, now Kantiv alternatives after the June 2026 rebrand, fall into six categories: proposal management suites, RFP (request for proposal) response tools, CRM (customer relationship management) proposal modules, shared drives and SharePoint folders, resume add-ons to a DAM (digital asset management system), and a system of record for people and project experience. Two things decide which one fits. Where is your bottleneck: drafting and compliance, or finding people and project data you can trust? And do you want that data inside one vendor's built-in AI, or structured so any AI tool your firm picks can use it?
Most teams start looking when a renewal or price review comes up, or when IT standardizes on Copilot, ChatGPT Enterprise or Claude and asks why proposal data lives somewhere else. Pick wrong and you pay for it on every bid. Buy a drafting tool when your real problem is 400 resumes in six formats across offices, and you get out-of-date experience written up faster.
One note on names: Kantiv is also an unrelated estimating and invoicing app for contractors. This guide is about Kantiv, the proposal platform for AEC (architecture, engineering and construction) firms. Flowcase sells in one of the six categories, and every test in this guide works on any vendor, including us.
Decide on data first. Are your people and project records clean, structured, kept current by the people who own them, and portable to any AI tool? AI output is only as good as the data underneath it.
What Kantiv is, and what it does well
Kantiv is the same company as Joist.ai under a new name: an AEC-focused pursuit intelligence platform for marketing and business development (BD) teams. Coverage of Kantiv AI's rebrand dates the official announcement to June 2, 2026.
Kantiv ingests the documents a firm already has, such as past proposals, resumes and project sheets, and uses its own built-in AI to organize them and draft from them. For AEC teams who want drafting help, that model has two real advantages: it is built specifically for AEC pursuits, and it starts quickly because it works from content the firm already owns.
Why proposal teams look at alternatives
The costliest trigger is a tool built for drafting in a firm where the slow part of every bid is finding resumes you can trust. Multi-office firms also run into these:
- M&A integration: an acquired office brings its own CV format and project list, and someone has to merge them before the first joint bid.
- Resume chaos: CVs live in SharePoint, Word files, spreadsheets, a homemade tool and a resume add-on to a DAM, and nobody is sure which version is current.
- CRM or ERP (enterprise resource planning) modernization: after a Salesforce, Workday, Maconomy or Certinia rollout, firms look for a dedicated expertise layer next.
As an illustration, picture the RFP landing on Thursday with the SF 330 (the federal architect-engineer qualifications form) due in 10 days. The key-personnel resumes sit in three offices, in three formats, and two of them still list a project manager who left last spring. No drafting tool fixes that week, because the trouble starts before anyone writes a word. Our bid and proposal management guide covers how to centralize experience data as part of a formal bid process.
Six kinds of Kantiv alternatives, and what each one is built to fix
Each category fixes a different bottleneck and stores your people data in a different place. Match the category to your bottleneck before you compare vendors.
Proposal management suites
These tools run the whole response workflow: content library, task assignment, review cycles and final assembly. They suit high-volume teams that want one workflow hub and a consistent process across pursuits. People data usually lives as content-library entries or uploaded resume documents, and someone has to keep them current. That library work never stops, and it usually lands on a proposal coordinator. For a closer look at how these tools handle formatting and content reuse, see proposal automation tools compared.
RFP response tools
These are built to reuse questions and answers at volume: questionnaires, standard answers and requirement tracking. They earn their keep for teams answering many Q&A-style RFPs and security questionnaires. They are not built around narrative resumes, project sheets or SF 330 forms. People data typically sits as answer text that someone updates by hand when a person's experience changes.
CRM proposal modules
These attach proposal features to opportunity records in your CRM, such as Salesforce, Microsoft Dynamics or HubSpot. They fit firms whose BD team already works in the CRM and wants pursuit data and proposals on one record. The CRM knows your opportunities and clients. It does not hold the detailed experience of each engineer or consultant, so resumes usually stay as attachments that someone re-uploads when they change.
Shared drives and SharePoint folders, with or without Copilot
Most teams already run this. It costs nothing extra, and at low bid volume in a single office it works. At scale it becomes the SharePoint folder of 400 resumes in six formats, with a coordinator acting as librarian. If you are weighing Kantiv against SharePoint plus Copilot, note that Copilot reads the documents as they are, so an out-of-date resume or an inconsistent project description flows straight into the draft. If the CV in the folder lists a 2021 role as current, the draft will too.
Resume add-ons to a DAM
These are resume features added to a system built for images, layouts and InDesign assets. They make sense for firms whose main pain is visual assets. Resumes and project data are a secondary feature, maintained by hand by whoever manages the files, and the core data model is built around files rather than people and their experience.
A system of record for people and project experience
This category holds people and project experience as structured records. Consultants and engineers maintain their own profiles and CVs, project sheets and reference projects sit alongside them, and anyone can search skills and experience across the whole firm. A bid team tailors a CV or project sheet for a specific bid and exports it in the firm's own templates. Flowcase is one example, used across engineering, consulting and legal by firms such as WSP, Sweco, DLA Piper and Capgemini.
It fits multi-office firms where the hard part is finding and trusting people and project data. It is not a full proposal management system or an AI writing tool. It does not run your RFP workflow, and many firms pair it with one of the categories above. Its scope is the people and project data that proposal tools and AI tools draw on.
The deciding question: can you take your people and project data to any AI tool?
Settle where your people and project data will live, and whether it can leave, before you compare drafting quality. Firms are choosing their enterprise AI tools now, and your proposal data will likely outlast whichever tool you pick in 2027.
Where your experience data lives in each option
- Kantiv: ingests your documents and uses its own built-in AI to organize them and draft from them. Kantiv relies on uploaded documents and its own built-in AI; ask how your data exports as structured records for other AI tools.
- Proposal management suites and RFP response tools: library content and answer text.
- CRM proposal modules: attachments on opportunity records.
- Shared drives and SharePoint: documents in folders.
- Resume add-ons to a DAM: files and assets.
- A system of record: structured, owner-maintained records with fields such as role, sector, project value, dates and certifications, which any AI tool can read.
Fields make the data queryable. Ask an AI tool for every structural engineer with healthcare projects over $50 million in the last five years, and it can answer from fields. From 400 Word files it has to infer from prose, and it will miss people.
Demo test: "Export every resume and project record as structured data, not PDFs, and show it working in the AI tool our firm already uses." A good answer is a live export in a machine-readable format. An evasive answer is "Our built-in AI already does that for you."
Built-in AI vs the AI your firm already chose
IT departments are standardizing on Copilot, ChatGPT Enterprise or Claude, and that choice can change. Respondents to the Thomson Reuters Future of Professionals study predicted AI would save professionals an average of 5 hours per week over the next year, yet only 22% said their business has a visible, defined AI strategy. With fewer than a quarter of firms holding a defined AI strategy, expect the AI tool on top of your proposal data to change.
Built-in AI ties your proposal data to one vendor's model and interface. A data layer that works with any AI tool lets you follow your firm's decision when it changes. Flowcase is not sold on its own AI; its job is keeping your people and project data clean and structured enough for whichever AI tool your firm uses.
What happens to your data if you switch
Ask every vendor four things: how you get your data back, in what format, how long it takes and what it costs. In Europe that question has a date attached. The EU Data Act switching rules entirely remove switching charges, including charges for data egress, from 12 January 2027. The regulation has applied since 12 September 2025.
That applies directly to firms in Sweden, Denmark and Germany. Elsewhere, treat it as a sign of where buyer expectations are heading, and check your own contracts with counsel. Wherever you are, a free export of 2,000 PDFs is a different thing from structured records you can load into your next system.
Who keeps resumes and project sheets current?
Three models are common:
Ingestion-based tools get you to a first draft faster on day one, and that is a fair advantage. The cost comes later. Any outdated role or project in those source documents reappears in each new bid until someone corrects it at the source.
Demo test: "Show me how an engineer updates their own profile in under five minutes, and how I see what changed since our last bid." An evasive answer is "You won't need to maintain anything."
Outputs: Word, PDF, InDesign and SF 330 from one dataset
Ask whether one structured record produces every format your bids require, in your own templates. If the SF 330 version of a resume is a separate document someone retypes, you are maintaining two resumes per person.
Under the FAR rules on SF 330, agencies use Part I to get a firm's qualifications for a specific contract when the contract amount is expected to exceed the simplified acquisition threshold, while Part II covers general professional qualifications. The current GSA SF 330 form carries a revision date of 07/2021, and on that form key-personnel resumes go in Part I, Section E. Confirm your templates match the version on GSA's site before you bid.
Outside federal work the same principle applies. Knowit's 26-partner consortium bid was a four-part frame-agreement response delivered in about 30 days, with tailored CVs exported from Flowcase in a custom template, and bid team members needed only a 30-minute session to learn the advanced features.
Demo test: "Produce SF 330 Section E resumes for five named people in our template, live."
Stack fit: a layer that sits alongside, or a hub that replaces?
Most options pitch themselves as the center of your stack. Ask instead which system is the source of truth for which data. Clients and opportunities belong in the CRM (Salesforce, Microsoft Dynamics, HubSpot) and employees in HR (Workday, SAP SuccessFactors). Projects and hours belong in the PSA (professional services automation) or ERP system, such as Deltek, Maconomy or Certinia. A people and project layer should sit alongside these, pull what they own, and feed proposals, with your chosen AI on top. Flowcase integrates with Salesforce, Microsoft Dynamics, Workday, SAP SuccessFactors, Deltek, Maconomy and Certinia, and replaces none of them.
Demo test: "Which fields do you sync from our HR and PSA systems, in which direction, and what happens on conflict?"
RFP analysis, compliance checks and drafting
If your bottleneck is reading 200-page RFPs and building the compliance matrix, proposal management suites and RFP response tools are the categories built for requirement analysis, compliance tracking, go/no-go support and drafting. Kantiv's model is built for reading RFPs and generating proposal content from the documents a firm uploads, using its own built-in AI. A system of record for people and project experience is not, and Flowcase does not claim to be.
Every vendor should also answer one baseline question in writing: "Is our data used to train AI models, where is it processed, and who can see it?" Treat a verbal-only answer as a warning.
Pricing, switching costs and total cost of ownership
Kantiv and the paid options in this guide sell on custom quotes, so get written quotes for the same scope. The license fee is the smaller part of the cost. Budget for migrating resumes out of mixed formats, cleaning the data, the hours spent keeping a content library current, retraining the team, and the cost of leaving later. Ask each vendor who runs the migration on their side and what they expect from yours.
Flowcase uses data import wizards, and a Customer Success team runs onboarding. In a Flowcase user survey, 56% rated setup "very easy", 16% rated it easier than other SaaS solutions, and 8% faced initial challenges. The same survey found that 56% of users save over 50 hours per month.
Kantiv and the alternatives at a glance
Who should pick which
Several of these options can run side by side.
What Kantiv's model is built for
Kantiv's model is built for AEC firms whose main bottleneck is turning past proposals into first drafts. It relies on static document storage and its own built-in AI, which limits what you can do with your people and project data outside Kantiv.
Choose a proposal management suite or RFP response tool if...
These tools still depend on the people and project data underneath being current, so plan for who maintains it.
Choose a system of record for people and project experience if...
It can sit alongside a suite or RFP response tool if you need both.
Stay on SharePoint for now if...
Your bid volume is low, you work from one office, and one person can still vouch for every resume. The signal to move is when building a bid means chasing people for updates and reformatting documents instead of tailoring content.
For the product-to-product view, see Flowcase and Kantiv side by side.
The one test to run before your next renewal or demo
Before your next call, send every shortlisted vendor the same request, Kantiv and Flowcase included: export 20 resumes and 10 project sheets as structured data, and load them into the AI tool your firm already uses. Watch whether the vendor runs the export live during the call. If it can't, and steers you back to its own built-in AI instead, assume your data will be hard to move when your firm changes AI tools.
Book a demo and ask us to run that test first.
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