Wordtune alternatives that are not Grammarly or ProWritingAid?

The tool that's worked well for our firm's process documentation is LanguageTool with its AI features enabled. It handles formal, structured writing better than most, and you can build custom dictionaries for industry terms. Their API is straightforward for Google Docs integration.

One caveat on training tools for specific jargon: most assistants still struggle with dense, technical statements. They'll sometimes rearrange logical dependencies in a way that changes meaning. You'll likely need to manually verify any complex procedural steps it suggests.

Have you considered using a general-purpose LLM API, like Anthropic's Claude, configured with a strong system prompt for your specific ERP domains? That's what we shifted to for client communications, as it offers more control over tone and terminology than packaged writing assistants.

Your focus on process-oriented writing and structured business logic narrows the field considerably. I've integrated several of these tools into enterprise workflows and can offer a more technical perspective on your criteria.

You're right to look beyond basic style checkers. For maintaining formal tone across longer documents, I'd suggest evaluating Hemingway Editor's API for its strict adherence to readability metrics you can calibrate. It's less about rewrites and more about enforcing a consistent complexity ceiling, which helps with procedural documentation. The API is RESTful and can be piped into a headless CMS with webhook triggers.

On your point about training tools on specific jargon, most SaaS writing assistants use a shared base model, making true domain adaptation difficult. A more effective, though technically involved, route is using a middleware layer between your content source and a generic LLM API (like Claude, as mentioned, or OpenAI). This layer can inject a terminology dictionary and predefined style rules into every prompt. This gives you the control for industry terms without the tool 'helpfully' rewriting your precise technical statements. The trade-off is you're now managing an integration pipeline, not just a subscription.

Regarding pricing transparency, you'll find most true API-based services are usage-metered, but watch for egress fees and compute time costs on your own middleware if you go that route. The vendor-locked platforms often hide these costs in seat licenses.

You're already hitting the main problem. Training the tool on specific jargon is where most of these platforms fail on security and compliance grounds. If you're feeding proprietary ERP terminology and process logic into a third-party AI, you're likely violating data handling agreements with your clients and creating an audit nightmare.

Most of these tools, even with custom dictionaries, send your text to their servers for processing. That's a hard no for any business writing that touches client data or internal procedures. The suggestion to use a general LLM API with a strong system prompt is the only viable path if you need true adaptation. Even then, you need a fully isolated, self-hosted setup. Anything else is just playing fast and loose with confidential information.

Yeah, user1291 makes a critical point about data privacy that a lot of teams overlook. Even tools that promise on-premise deployment often phone home for processing unless you're on their enterprise tier, which is a total dealbreaker.

That's exactly why we moved to using OpenAI's API through an internal proxy that strips all metadata and logs nothing. It's not perfect, but it's a compromise between using a powerful model and keeping client data off some random SaaS server. You still have to trust the LLM provider, but at least you're not also trusting the middleman tool's security.

It's a messy landscape for anything confidential.

Your point about the Hemingway API is solid for enforcing readability, but it's a purely mechanical gate. It'll flag a complex sentence about a multi-step inventory reconciliation, but it won't understand if the rewritten simpler version breaks the causal logic. It's a good pre-flight check, not a co-pilot.

The middleware layer suggestion is the correct architectural pattern for this. The critical implementation detail you gloss over is prompt chaining. You don't want a single prompt stuffed with a dictionary and rules; you degrade performance fast. You need at least two stages: one to analyze the text structure against your style guide, and a separate, constrained rewrite step that uses the analysis output. That keeps the token count manageable and the model's "creativity" on a shorter leash.

The real bottleneck becomes maintaining that terminology dictionary and rule set as your business logic evolves. It's a manual, brittle process. You're essentially building a small product.

Exactly. Prompt chaining isn't a magic bullet, it's just shifting the labor. You've now traded one vendor's pricing tiers for a full time job managing your own prompt taxonomy.

>The real bottleneck becomes maintaining that terminology dictionary and rule set
That's the part everyone undersells. I've seen teams burn months curating a "living" style guide for an LLM, only to have a minor product update introduce a new term that breaks every related rewrite rule. The maintenance overhead has a real cost that evaporates the supposed ROI of avoiding a SaaS subscription.

You're not building a small product, you're adopting a pet with very specific dietary needs.

Totally get the need for something that handles technical flow, not just grammar. For process docs, we've had decent luck with Writer - they let you bake in a style guide and glossary at the API level, so it sticks closer to your specific terms (like "SKU rationalization" in our case). It won't magically understand logic, but the custom rules help it avoid over-simplifying.

That said, the training curve is real. We spent a couple weeks fine-tuning the style guide before it stopped trying to "fix" our standard procedure headings. The API is solid for Google Docs and Notion though, and you only pay for what you process.

How much of your internal style guide is already formalized? That's the biggest time-suck if you're starting from scratch.

You're asking for a unicorn. The consistent formal tone across long docs? No off-the-shelf tool does that well, they all drift. Your bigger issue is the jargon support. Building a custom dictionary is a trap. You'll spend more time maintaining the term list and fighting false positives than you save on writing.

You mention transparent, usage-based pricing. That just means you're paying per API call for a service that still can't grasp your business logic. The cost will be the hours your team wastes correcting its logical missteps.

The hands-on experience you want is this: they all over-simplify complex statements. The learning curve is vertical and never ends.