Built different.
On purpose.

Most tools in this space solve one slice. Search. Or wiki. Or support bot. We built the layer that connects them. A brain for your business.

What we do. What they don't.

Foundation

Builds your brain automatically.

Auto-extracts a knowledge graph from your docs on upload. Most platforms make you build the graph yourself, or skip the graph entirely.

Honesty

Knows what it doesn't know.

Flags gaps in your knowledge, names the right expert, drafts what should be there. Nobody else does this.

Quality

Catches contradictions before your team does.

Same refund window. Same appointment policy. Same brand standard. Every shift, every location, every channel.

Reach

Talk to it from anywhere.

Voice on the floor. Tablet in the truck. Kiosk behind the line. Wherever your team works, the brain works there too.

Learning

Every conversation makes it smarter.

Every question, every answer, every correction tightens the brain. No extra documentation work.

Scale

Same brain, every location.

Opening a new location next month? The playbook is already loaded. Day one feels like month three.

And one more thing

Flat pricing. No per-seat tax. No per-resolution charges. No $5M minimums.

Five great categories. And why we built something different.

These are excellent tools. They each solve a real problem really well. Here's where each one shines, and why we made different architectural bets.

Category

Enterprise search tools

Tools that search across many SaaS apps with AI grounding.

Enterprise search platforms are world-class at one job: making everything you already have searchable. If your team works across dozens of SaaS tools and the goal is one place to find anything, they nail it. Built for companies with mature stacks and dedicated IT teams.

They're read-only by design. That's not a flaw, it's the architecture they picked. Aggregation over creation. Retrieval over generation.

We believe the most valuable knowledge in your company is the part that hasn't been written down yet. So we built a brain that finds what exists, tells you what's missing, and helps your team close the gap.

If 'make my existing tools searchable' is the job, they're the right tool. If 'make my company's knowledge keep getting better' is the job, that's where we come in.

Category

Intelligence platforms

Enterprise data platforms that combine search, analytics, and AI.

Intelligence platforms are some of the most sophisticated software ever shipped. World-class at combining structured data, unstructured data, and AI at a scale that handles governments and Fortune 50 operations. If your problem is that big, nothing else comes close.

That power comes with deliberate trade-offs. Implementation timelines in quarters. Professional services dependence. Contract minimums in the millions. That's not a downside, it's what powering nation-scale problems looks like.

We built Simply Asking for the team between 'spreadsheet' and 'Palantir'. So we made the platform self-serve, the pricing flat, and the time-to-value measured in days.

If you're a global enterprise with the budget to match, they're worth every dollar. If you want a brain that grows with you starting next Tuesday, that's us.

Category

Team wiki tools

Knowledge cards your team writes and maintains by hand.

Team wikis are excellent writing surfaces. Verified, hand-curated answers, surfaced where you work. For a small team with one dedicated curator, the simplicity is the feature.

The choice to be human-curated is what makes them simple. It's also what makes them strain the moment your team grows past one curator. That's a design philosophy, not a bug: trust the humans to maintain the source of truth.

We took a different bet. The knowledge sitting in your existing documents, conversations, and tools should connect itself without anyone writing a card. So we built a brain that ingests what already exists, extracts the relationships automatically, and keeps the map current as the source material changes.

If your team loves the discipline of card-by-card knowledge management, wikis are wonderful. If you'd rather your existing work become the knowledge base automatically, we built that.

Category

Support chatbots

Deflection bots on a single vendor's chat widget.

Support chatbots are tuned for one job and they do it well: deflect tickets on a single channel, usually a chat widget. If most of your customer interactions live in one vendor's ecosystem and the metric is deflection rate, the focus pays off.

That focus is also the architectural commitment. The bot lives inside one vendor's stack. Per-resolution pricing. No shared knowledge layer with the rest of your business. That's not a flaw, it's the trade-off that comes with building a category-specific product.

We approached it from the other direction. We built the knowledge layer first, then made agents a feature on top of it. The same brain that answers a customer in chat also answers your sales rep in Slack and your operator on a warehouse tablet.

If chat-only deflection at the highest possible rate is the job, support-specific bots are built for it. If you want one brain across every surface where your team and customers ask questions, that's why we exist.

Category

Graph databases

Infrastructure for storing and querying knowledge graphs.

Graph databases are the gold standard for storing and querying graph data. World-class engines, mature tooling, vibrant developer ecosystems. If you have a team with graph engineering expertise and a clear data model in mind, they give you complete control.

The deliberate choice is that they're infrastructure. The graph is yours to build. Model every node and edge, write the ETL, design the queries, build the interface. That's not a downside, it's the contract you sign when you pick a database over a platform.

We chose the opposite trade-off. Most teams don't want to build a graph, they want to use one. So we auto-extract entities and relationships from your documents on upload, surface the connections through a chat and search UI, and skip the infrastructure project entirely.

If graph modeling is core to your engineering practice, graph databases are unbeatable. If you just want the benefits of a knowledge graph without building one, that's where we come in.

Common questions.

Yes, those are exactly who we built for.

Service businesses (including home service teams), hospitality and restaurants, multi-location franchises, and retail operations all share the same problem. Critical knowledge lives in people's heads, in scattered documents, and in past conversations. When someone leaves, when a new location opens, when a new hire starts, that knowledge has to be findable, current, and trustworthy.

We're tuned for operationally complex businesses at human scale. Not defense procurement. Not hospital systems with HITRUST mandates. The teams between 'spreadsheet' and 'enterprise platform', where one person knowing the answer isn't enough anymore.

If your business runs across multiple locations, depends on consistent operations, or struggles to onboard new people fast enough, we're built for you.

Enterprise search platforms are world-class at one job. Making everything you already have searchable. Tools like Glean and Coveo nail that experience for companies with mature stacks and dedicated IT teams.

They're read-only by design. That's the architectural choice. They aggregate, they don't create.

We took a different bet. The most valuable knowledge in your company is the part that hasn't been written down yet. So we built a brain that does three things they don't:

  • Tells you what's missing
  • Identifies the right expert to fill the gap
  • Helps your team draft what should be there

If 'make my existing tools searchable' is the job, they're the right tool. If 'make my company's knowledge keep getting better' is the job, that's where we come in.

Open-source search tools like Onyx (formerly Danswer) and GoSearch are excellent if self-hosting is a strength your team wants to invest in. Full control, no vendor lock-in, transparent code, and the freedom to customize every layer. For an engineering team that loves owning infrastructure, that's the right trade.

The architectural commitment is that the work moves to you. You operate the search service, manage the connectors, handle the upgrades, tune the models, and own the uptime. That's not a flaw, it's what choosing self-hosted open-source means.

We took a different bet. Most teams want the result, not the operational burden. So we built a managed brain that ships with the connectors, the model routing, the upgrades, the citations, and the gap detection already wired together. You point it at your knowledge and start asking.

If your superpower is self-hosting open-source infrastructure, Onyx and similar projects are terrific. If you'd rather plug in this afternoon and ask your first question by dinner, that's why we exist.

Team wikis like Guru and Notion are excellent writing surfaces. For a small team with one dedicated curator, the simplicity is the feature. Verified, hand-curated answers surfaced where you work.

The trade-off is that everything is manual:

  • Humans write every card
  • Humans tag every card
  • Humans keep every card current

That's not a flaw, it's a design philosophy. Trust the humans to maintain the source of truth.

We took a different bet. The knowledge sitting in your existing documents, conversations, and tools should connect itself, without anyone writing a card. So we ingest what you already have and auto-extract the relationships into a graph that updates as the source material changes.

If your team loves the discipline of card-by-card knowledge management, wikis are wonderful. If you'd rather your existing work become the knowledge base automatically, we built that.

Productivity-suite AI is excellent at one job. Helping you work faster inside that suite. Copilot for Outlook, Notion AI for Notion pages. Sharp tools for the contexts they live in.

The architectural commitment is that they live inside their parent suite. They don't:

  • Connect to your other knowledge sources
  • Detect what's missing across your company
  • Generate the missing content
  • Surface answers wherever your team works

That's not a weakness, it's the boundary of being a feature on top of one tool.

We built the layer underneath. The same brain that answers your sales rep in Slack also answers your operator on a warehouse tablet and your developer in their editor. One knowledge source, every surface.

If most of your work happens inside one productivity suite, Copilot or Notion AI fit perfectly. If you want a brain that works across all your tools and all your people, that's where we come in.

Google's NotebookLM is brilliant at one job. You upload a handful of PDFs, ask questions, get cited answers. For a researcher with a curated reading list or a student studying for an exam, the simplicity is exactly the point.

The architectural choice is that each notebook is its own world. You build the notebook, you maintain the notebook, and it stays inside Google's interface. No team layer, no integrations into the tools your business already uses, no memory of what's missing across your knowledge.

We built the other half. Your business doesn't store knowledge in a single notebook. It sprawls across documents, conversations, integrations, and people. So we ingest all of it into one connected brain, auto-extract the relationships, surface answers wherever your team works, and tell you what's still missing.

If you want a research tool for a small set of files, NotebookLM is wonderful. If you want a brain for your whole business that lives where your team already works, that's where we come in.

Graph databases like Neo4j are the gold standard for storing and querying graph data. World-class engines, mature tooling, and a vibrant developer community. If you have graph engineering expertise and a clear data model, they give you complete control.

The architectural choice is that they're infrastructure. The graph is yours to build:

  • Model every node and edge
  • Write the ETL pipelines
  • Design the queries
  • Build the UI on top

Budget six figures and 3 to 6 months for the graph layer alone.

We chose the opposite trade-off. Most teams don't want to build a graph, they want to use one. So we auto-extract entities and relationships from your documents on upload, surface the connections through chat and search, and skip the infrastructure project entirely.

If graph modeling is core to your engineering practice, Neo4j is unbeatable. If you just want the benefits of a knowledge graph without building one, that's where we come in.

We don't compete with them, we use them.

ChatGPT, Claude, and Gemini are some of the most impressive AI tools ever shipped. They're foundation models, world-class at general knowledge, reasoning, and writing. Inside Simply Asking, we route each task to the model that's best at it. Different models for routing, drafting, reasoning, vision. OpenAI here, Anthropic there, Google somewhere else.

What foundation models can't do on their own:

  • Read your files
  • Search your knowledge
  • Cite a source
  • Tell you what's missing

That's not a flaw, it's what "trained on the internet, not on your company" means.

Simply Asking is the layer that sits on top. We connect your knowledge (documents, conversations, recordings, integrations), map the relationships between them, and route every question through the right foundation model with your business as the source of truth. Every answer is grounded in your actual content with a citation.

If you want a brilliant generalist, ChatGPT or Claude are remarkable. If you want a brain that combines those models with your company's truth, one answer routed through multiple foundation models and fully grounded, that's why we exist.

Most enterprise platforms in this space measure setup in months. First module in 90 days. Six-figure professional services engagements. Quarterly steering committees before a single user logs in. That's a real choice. For the customers paying for it, the long runway is part of how trust gets built.

We made a different bet. Service businesses, hospitality teams, multi-location franchises, and retail operators don't have 90 days. So we built Simply Asking to be live this afternoon. Connect your first knowledge source in minutes. Ask your first question by lunch. Roll it out to your team by Friday.

That speed isn't a corner cut, it's a different architecture. Managed connectors. Sensible defaults. A platform you grow into instead of a project you survive.

If your buying motion includes a 12-month deployment plan, the enterprise platforms are built for that. If you want a brain in your business by the end of the day, that's where we come in.

Different product, similar name. Anaconda's Lumen AI is an open-source tool for data scientists to explore tabular data with natural language. Built for analysts and engineers working in Python notebooks.

Our Lumen is the chat interface for your business knowledge. The voice you ask questions to, that pulls answers from your documents, conversations, and integrations, with a citation back to the source. Built for operators, managers, frontline teams, and the people who actually run your business.

Same word, very different jobs. If you're looking for the Anaconda product, search 'Lumen AI HoloViz'. They're at lumen.holoviz.org. If you want the brain for your business, that's us.

We're not the right answer for everyone, and we'd rather tell you upfront. Four cases where another tool is the better choice:

  1. You need to search hundreds of SaaS tools and don't care about closing knowledge gaps. An enterprise search platform like Glean will serve you better.
  2. You have a $5M+ budget and need government-grade compliance with massive data complexity. Intelligence platforms like Palantir are built for exactly that.
  3. You only need a deflection bot on a single vendor's chat widget. A purpose-built support bot like Intercom Fin is tuned for it.
  4. You're a defense contractor, hospital system, or other regulated enterprise with a 12-month procurement cycle, FedRAMP or HITRUST mandates, and an in-house IT team to run the implementation. Specialized GraphRAG platforms built for that environment will fit you better.

For everything in between, making your company's knowledge findable, current, and useful across every surface, we're the right tool. We'd rather earn your trust by being honest about fit than oversell.