Your AI doesn’t know what it doesn’t have.
GammaLex builds context intelligence for AI agents. Starting where precision matters most: precision medicine, where the right context changes the outcome.
Your AI agent is only as good as the context it starts with, and no one is checking that context.
What changed since this patient’s last visit?
Without GammaLex
“The care plan says to continue the current dose, so we can rely on it.”
With GammaLex
“Not yet. I couldn't find every medication change, and the care plan disagrees with the pharmacy record. I'll resolve the contradiction before acting.”
Meet the GammaLex Context Engine
Know if your agent has enough context to act.
The GammaLex Context Engine determines what the request depends on, gathers it from authorized systems, and checks whether the context is enough before your agent acts.
Request
Who is asking, and about what.
GammaLexAgentSDKDetermine
The context engine determines what the decision depends on, using the rules you set.
GammaLexPatient P-2041 — changes since last visitBefore any readTo decide this, the context engine needs:
Last visitRequired
Nothing can be compared until the last visit is in hand.
412 records permitted · 1,906 excluded
Gather
It gathers only that, from authorized systems. Anything off-limits stays out, and is flagged.
GammaLexcontext6 selectedLast visit note (2026-01-14)Records system
The last visit, which everything else is compared against.
6 records read · 1 withheld
Connect
How the records relate: which medication change builds on which, where records conflict, what depends on what.
GammaLexcontext graph6 recordsPharmacy record: dose reducedConflict · Pharmacy feed
Shows the dose was reduced.
Evaluate & Learn
It evaluates whether the context is enough for the request, shows the evidence, and remembers the run so the next request starts from what is established.
GammaLexRUN_7D41C2CheckedCare plan and pharmacy agreeContradictory
The care plan says to continue the current dose. The pharmacy record shows the dose was reduced.
1 of 5 established
One call before your agent acts, through the SDK, API or MCP, with the model and sources you already use. How it connects
Not retrieval. Not guardrails. The layer in between.
LLM
Reasons
Thinks with what it is given.
RAG
Retrieves
Finds relevant information.
Guardrails
Constrains
Limit what an agent can say or do.
GammaLex
Contextualizes
Evaluates rules deterministically against evidence before the agent acts.
Checks that rely on LLMs can answer differently each time. GammaLex evaluates your rules deterministically—so the same evidence always produces the same verdict, and every verdict exposes the exact trail it rests on.
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