Stored context, made visible.
Behind the scenes, FELLOW hands bounded, cited context to a model, not a bag of similar chunks. This page is the other half: what that same context looks like when a human can read it, and correct it, directly.
A map for truth. A search net for scale.
Vector retrieval is excellent at “find something like this.” It is a bad design choice for “what is our canonical definition,” “who reports to whom,” or “what stage is this buyer in.” FELLOW is built as a hybrid: governed structure for high-stakes claims, retrieval for exploration.
| Dimension | RAG-only pipeline | FELLOW |
|---|---|---|
| Core unit | Fragmented text chunks in a vector index | Atomic facts with evidence, linked into shapes |
| How answers are found | Probabilistic nearest-neighbor similarity | Structured + graph paths first; semantic when you explore |
| Structure | Chunking often flattens tables, stages, and reporting lines | Org charts, process maps, and personas assembled from links |
| Staleness | An outdated but similar chunk can rank highest | Supersession and provenance; current state is explicit |
| Human interface | Query a black-box index; hard to correct in place | Readable views; edits flow through the same review path |
| Honesty about absence | Missing context is usually silent (or hallucinated) | Known gaps are first-class and actionable |
| Best fit | Wide, fuzzy search over archives | Canonical account knowledge agents and teams act on |
Hybrid in practice
Asking a probabilistic system for your company’s high-stakes commercial truth is the wrong job for that tool. Keep search for scale; put reviewed structure under decisions. More in the blog →
The same context, three shapes.
FELLOW doesn't have one generic viewer. It renders each record type into the form a person actually expects (an org chart, a process map, a profile), never a raw JSON blob.
Reporting lines assembled from graph-linked facts ("Richard reports to Gavin," "Dinesh reports to Gavin"), not a synced org-chart import.
Currently: pricing objection raised on last call, procurement now looped in. Stage advanced automatically when that objection was logged.
A buyer's stage isn't a picklist a rep sets by hand; it moves when the underlying evidence changes.
Erlich B.
Economic buyer · Champion
- Prefers monthly retainer over fixed-scope project[1]
- Skeptical of "vapor," wants proof before commitment[2]
- Reports to a historically cost-sensitive buyer[3]
Every attribute is a cited assertion, not a free-text CRM note: click through to the source conversation.
Every shape is built from cited facts.
The visualizations aren't the data; they're a view of it. Underneath each one is a set of individual, traceable assertions.
"Richard Hendricks reports to Gavin Belson (VP Sales)."
Traces to
- kickoff-call · 2026-04-02 · 00:12:44[1]
- org-announcement.pdf: p.2[2]
State
- current · supersedes fct_03X8 (Q4 structure)
Traceable back to the moment it was said.
Every node in a chart, every stage on a map, every line on a profile is one assertion with a source attached. Follow it back to the exact clause or timestamp, and see what it superseded.
- Source-linked at the level of the individual fact
- Supersession tracked, so nothing stale is shown as current
- Corrections flow back through the same review path
What we don't yet know
- Signing authority above $50k: unconfirmedgap
- Incumbent vendor & contract end dategap
- Security review requirement: implied, unverifiedgap
And it shows you what's still missing.
A profile with holes shouldn't look complete. FELLOW tracks the questions it can't yet answer for a record and surfaces them, so the next call, or the next agent run, knows exactly what to go find.
- Missing facts flagged rather than silently guessed
- Gaps become a concrete discovery checklist
- Agents can request precisely what's absent
What's shipping next.
Built in the open, in dependency order: each phase unlocks real usage, not a demo.
Multi-channel access
Query and update FELLOW from where work already happens, starting with Slack, using per-person keys so every request is tied to a real identity, not a shared token.
Auto-capture from conversation
A session with an agent or a colleague turns directly into knowledge: extracted, scored, and immediately usable, with review reserved for the cases that actually need a second look.
Visual interface
This page is the preview: the same read surface shown above, plus the ability to correct, add, or promote a record without leaving the view it was rendered in.
Structured document ingestion
Long, structured source documents (filings, contracts, policy manuals) decomposed into linked, queryable records, with the full source always one reference away.